Instruction:
I want to consolidate the admission variables actually used by several prediction schemes in this 2020 COVID-19 mortality risk prediction paper into a single line, to make it easy to see which variables overlap and which appear only in the comparison schemes.
Please follow the steps below. First, locate the target paper — a 2020 open-access review whose title contains all of "prognosis model", "mortality risk", and "COVID-19", and whose main text discusses hospitalized patients in Wuhan.
Then, retain only two types of variables:
- Type 1: admission variables that appear in both the Random Forest and XGBoost variable importance rankings.
- Type 2: additional admission variables that do not appear in both rankings but are present in the CURB-65 or NEWS schemes used by the authors for comparison.
Next, for each retained variable, record it in the following format:
variable~RF_rank_or_0~XGB_rank_or_0~F~C~N~X
Where:
- RF_rank_or_0: the rank of this variable in the Random Forest ranking; write 0 if it is not included.
- XGB_rank_or_0: the rank of this variable in the XGBoost ranking used in the paper; write 0 if it is not included.
- F: whether this variable entered the authors' final logistic regression model.
- C: whether this variable belongs to CURB-65.
- N: whether this variable belongs to NEWS.
- X: whether this variable belongs to the XGBoost model used as a comparison in the paper.
Finally, sort all variables alphabetically by variable name, join them with | into a single line; if the paper cannot be found, output NONE.

First, locate the target paper: a 2020 open-access review whose title contains all of "prognosis model", "mortality risk", and "COVID-19", and whose main text discusses hospitalized patients in Wuhan.

Retain only two types of variables: admission variables that appear in both the Random Forest and XGBoost rankings; or variables that do not appear in both rankings but are additional items belonging to CURB-65 or NEWS.

For each variable, annotate it as required with RF rank, XGB rank, and whether it belongs to the final logistic regression, CURB-65, NEWS, and the comparison XGBoost model, then output in alphabetical order by variable name.

Europe PMC search results and the target open-access article yield the candidate Wuhan COVID mortality-risk review

article tables and discussion sections yield RF/XGBoost rankings, final logistic-regression inclusion, and comparator-variable memberships for CURB-65 / NEWS / external XGBoost

final rows are produced only after overlapping variables and comparator-only variables are merged into one normalized variable table

comparator-only variables must be captured from the discussion definitions rather than from Table 2 + Table 3 alone

comparator membership must be read from the article's explicit scheme definitions rather than inferred from common clinical usage

variable normalization must wait until RF/XGBoost overlap and comparator-only additions are both complete

the 2020 open-access COVID-19 mortality-risk review about Wuhan inpatients; variable inclusion and comparator definitions are taken from the article's current full-text tables and discussion

Exclude admission variables that do not appear in both RF and XGB rankings and also do not belong to CURB-65 / NEWS additional variables.

Exclude results that stop at Table 2 + Table 3 and do not proceed to the discussion to read the comparator definitions.

Exclude results that infer comparator variables by common sense rather than verifying against the paper's explicit definitions.

variable RF_rank_or_0 XGB_rank_or_0 F C N X

use the variable wording normalized in the article tables; keep `Systolic pressure` and `Diastolic pressure` as separate variables

RF_rank_or_0 and XGB_rank_or_0 are positive integer ranks when present, otherwise 0

F, C, N, and X are emitted as 1 or 0 only

the shared variable set from Table 2 and Table 3 is fully resolved

the comparator definitions for CURB-65, NEWS, and the comparison XGBoost model are fixed before the final line is emitted


Instruction:
Track studies that were Phase 1 in the 2021 Alzheimer's disease drug development pipeline review by their ClinicalTrials.gov identifier, and check whether they continue to appear in the 2022 and 2023 pipeline reviews.
Follow these steps. First, locate the three articles: the 2021 review titled "Alzheimer's disease drug development pipeline", and the 2022 and 2023 open-access reviews in the same series.
In the 2021 review, retain only the studies that were listed as Phase 1 at that time.
Then, in the 2022 and 2023 reviews, check each of these studies one by one, but match them by the same ClinicalTrials.gov identifier rather than by drug name alone, because drug names can change across years.
Finally, keep only those studies that can still be found under the same ClinicalTrials.gov identifier in both 2022 and 2023. Format the result as a single line: NCT~2021_agent~2022_phase~2022_agent~2023_phase~2023_agent. Sort by NCT in ascending order and join records with |. If the set of three articles cannot be found, output NONE.

Use only the Phase 1 studies from the 2021 Alzheimer's disease drug development pipeline article as the baseline.

Retention in 2022 and 2023 must be determined by exact match on the ClinicalTrials.gov NCT identifier, not by drug name alone.

Keep only studies that are found under the same NCT in both 2022 and 2023, and output them sorted by NCT in ascending order.

the 2021, 2022, and 2023 pipeline reviews yield the 2021 Phase 1 baseline cohort and the later-year lookup tables

article tables yield exact ClinicalTrials.gov NCT IDs, yearly phase labels, and yearly drug names for the same study

final rows are produced only after 2021 baseline studies are re-identified in both later reviews by exact NCT matching

continuation must be matched by exact NCT rather than by drug name, because drug names drift across years

2022 and 2023 lookups must use the fixed 2021 Phase 1 NCT set as the starting cohort rather than later-year table membership alone

yearly phase/name fields are only valid after the same NCT is confirmed across all three reviews

the 2021, 2022, and 2023 open-access Alzheimer's disease drug development pipeline reviews; the baseline is the 2021 Phase 1 cohort and continuation is matched by exact ClinicalTrials.gov NCT

Exclude results that are continued by drug name alone without an exact match on the same ClinicalTrials.gov identifier.

Exclude studies found only in 2022 or only in 2023, not continuously retained in both years.

Exclude studies not in the 2021 baseline Phase 1 set.

use the exact ClinicalTrials.gov identifier as the cross-year identity key

normalize phases to P1, P2, or P3; if the same NCT appears multiple times in a year, keep the highest phase for that year

keep the agent text as shown in each year-specific table


Instruction:
I want to see which candidate molecules predicted in the 2023 "Antibodies to Watch" article as expected to submit their first marketing applications in 2022–2023 have actually been approved or entered first regulatory review in the 2024 installment of the same series.
Follow the steps below. First, find the open-access full texts of both the 2023 and 2024 "Antibodies to Watch" articles in Europe PMC.
Then, in the 2023 article, identify all candidate molecules listed as **"expected to submit first marketing applications in 2022–2023"**.
Next, check each of these molecules against the 2024 article and retain only those that have been approved or have entered first regulatory review.
Finally, format each qualifying molecule as follows:
INN~2023 category~2023 prediction label~2024 status~2024 indication~2024 region
where:
	•	2023 category uses NC/CA for non-cancer/cancer;
	•	2024 status uses A/R for first approval/first regulatory review.
Sort by INN alphabetically and output as a single line joined by |; if neither article is found, output NONE.

Cosibelimab~CA~MAA,Q2 2023~R~Squamous cell carcinoma~US|Elranatamab~CA~2023~A~Multiple myeloma~US,EU,Switzerland,Brazil|Garadacimab~NC~BLA,2023~R~Hereditary angioedema~EU|Odronextamab~CA~BLA,H2 2022~R~Diffuse large B-cell lymphoma~US,EU|Pozelimab~NC~BLA,H2 2022~A~CHAPLE disease~US|Suciraslimab~NC~NDA,2023~R~Rheumatoid arthritis~China|Talquetamab~CA~2023–25~A~Multiple myeloma~US,EU,UK,Switzerland|Zolbetuximab~CA~BLA,2023~R~HER2-negative gastric or gastroesophageal junction adenocarcinoma~US,EU,Japan,China

First, identify all candidate molecules in the 2023 Antibodies to Watch article that are predicted to submit first marketing applications in 2022-2023.

Then, check each of these molecules against the 2024 article and retain only those that have been first approved or have entered first regulatory review.

The 2024 status must distinguish A=first approval from R=first regulatory review, and include the 2024 indication and region.

the 2023 Antibodies to Watch article yields the forecast baseline of candidates expected to file in 2022-2023

the 2024 article tables yield first-approval outcomes, first-regulatory-review outcomes, indications, and regions for the same INNs

final rows are produced only after Table 1 approvals and Table 2 first-review candidates are merged back onto the 2023 forecast cohort

both 2024 Table 1 and Table 2 must be read so that first-review-but-not-yet-approved candidates are retained

2024 status coding must distinguish approval from first regulatory review instead of collapsing both into a single positive match

region and indication fields are valid only after the 2023 forecast cohort is reconciled against both 2024 tables

the 2023 and 2024 open-access Antibodies to Watch articles; baseline candidates come from the 2023 forecast set and 2024 outcomes come from current Table 1 plus Table 2

Exclude results that only check approvals in 2024 Table 1 without also consulting Table 2 for first regulatory review candidates.

Exclude molecules not in the 2023 forecast baseline.

Exclude candidates that were neither first approved nor entered first regulatory review in 2024.

keep the label content inside the parentheses and remove spaces after commas, for example `BLA,H2 2022`

emit `A` for first approval and `R` for first regulatory review

preserve the raw region string but remove spaces after commas, for example `US,EU`


Instruction:
I am evaluating the accuracy of annual antibody drug watchlist predictions and want to trace whether the 2022 cohort of candidates from the Antibodies to Watch series simply experienced delays in development progress. I need you to use the Europe PMC database to systematically map the year-over-year status changes for these candidates.

First, establish the literature baseline and initial candidate set. Precisely locate the three open-access full-text Antibodies to Watch articles published in 2022, 2023, and 2024 in Europe PMC. Once all three articles are found, identify a set of antibodies (INN) with a specific delay pattern: those that were explicitly listed in the 2022 article under a category such as "expected to file soon" (identified by INN, drug code, project name, or other recognizable name) but, due to slower progress, still remained as watchlist candidates in the 2023 article.

Second, determine the latest status of these consecutively delayed candidates. For the identified antibody group, ascertain their final status in the 2024 article: whether they finally received first approval, are in first regulatory review, remain on the 2024 watchlist, or have completely disappeared from the 2024 main article list.

Finally, after completing the cross-year literature review and status confirmation, aggregate the extracted parameters into a specific formatted single-line record. If all three target articles cannot be found, output NONE. If all three are successfully located, concatenate the internal parameters for each qualifying antibody in the fixed order "INN~2022 category~2022 phase~2023 prediction label~2024 status~2024 phase or NA~2024 indication or NA~2024 region or NA". Then join all identified candidates in strict alphabetical order by INN using the "|" symbol into a single string with no spaces.

If all three target articles cannot be found, output NONE. If all three are successfully located, concatenate the internal parameters for each qualifying antibody in the fixed order "INN~2022 category~2022 phase~2023 prediction label~2024 status~2024 phase or NA~2024 indication or NA~2024 region or NA". Then, join all identified candidates in strict alphabetical order by INN using the "|" symbol into a single string with no spaces.

Apamistamab-I-131~CA~P3~BLA,H1 2023~F~P3~Ablation of bone marrow prior to transplantation in AML patients~NA|Bentracimab~NC~P3~BLA,Q4 2022~F~P3~Reversal of the antiplatelet effects of ticagrelor~NA|Cosibelimab~CA~P3~MAA,Q2 2023~R~NA~Squamous cell carcinoma~US|Erfonrilimab~CA~P3~NDA~F~P3~Pancreatic ductal adenocarcinoma~NA|Odronextamab~CA~P2~BLA,H2 2022~R~NA~Diffuse large B-cell lymphoma~US,EU|Talquetamab~CA~P2~2023-25~A~NA~Multiple myeloma~US,EU,UK,Switzerland|Tiragolumab~CA~P3~2023~F~P3~NSCLC~NA|Zanidatamab~CA~P2~2023~D~NA~NA~NA|Zolbetuximab~CA~P3~BLA,2023~R~NA~HER2-negative gastric or gastroesophageal junction adenocarcinoma~US,EU,Japan,China

Start with the 2022 Antibodies to Watch candidates listed as "expected to file soon", but retain only those molecules that still remain as watchlist candidates in the 2023 article of the same series.

For these consecutively delayed candidates, determine their final status in the 2024 article: first approved, in first regulatory review, or completely absent from Tables 1-4.

Name matching must handle the Apamistamab naming drift; complete absence in 2024 must be explicitly encoded as D.

the 2022, 2023, and 2024 Antibodies to Watch articles yield the 2022 soon-to-file baseline, 2023 carry-over membership, and 2024 status tables

article tables and full-text naming context yield name normalizations, 2024 table presence/absence, and final status labels for each carried-over INN

final rows are produced only after 2022 candidates are filtered by 2023 carry-over status and then resolved against 2024 Tables 1-4 plus explicit absence

2022 candidates must first be filtered by 2023 carry-over status before they are matched against the 2024 tables

Apamistamab naming drift forces explicit normalization before 2024 lookup

complete 2024 absence must be emitted as D rather than treated as a lookup failure

the 2022, 2023, and 2024 open-access Antibodies to Watch articles; the 2022 baseline is filtered by 2023 carry-over status and then checked against 2024 Tables 1-4, with explicit absence retained as a status

Exclude results that directly match the 2022 baseline against 2024 without applying the 2023 carry-over filter.

Exclude matching results that do not handle the Apamistamab naming drift.

Exclude cases where complete 2024 absence is treated as a lookup failure rather than a status that must be output.

normalize stage labels such as `Phase 3` to `P3` and `Pivotal Phase 2` to `P2`

keep the label content inside the parentheses and remove spaces after commas, for example `BLA,H1 2023`

emit one of `A`, `R`, `F`, or `D` exactly

if status is A or R, phase_or_NA_2024 must be `NA` and region_or_NA_2024 must carry the raw region string; if status is F, region_or_NA_2024 is `NA` and phase_or_NA_2024 carries the normalized phase; if status is D, all three trailing 2024 fields are `NA`

preserve the fixed source exception around the Apamistamab-I-131 naming variant instead of over-normalizing the INN


Instruction:
I am compiling a cross-platform correspondence checklist for core predictors of COVID-19 hospitalization prognosis. Using the Europe PMC database, I need to work through the process of identifying the variables each specific model actually used, together with their matching attributes.

First, establish the literature baseline. In Europe PMC, precisely locate the 2024 WHO global individual patient data validation paper and identify the four prognostic models that were successfully externally validated in low- and middle-income country data. Then trace back to the three original model papers corresponding to these four models.

After locating these four target papers, the core task is to extract and verify the specific characteristics of the predictors. Determine which distinct admission variables each of the four models actually used in the evaluation. For each identified variable, clarify its acquisition pathway in the WHO platform baseline table: either a direct match under the same or a substantively equivalent name (marked as E), or a fixed mapped conversion (marked as M). Also trace the model-source attributes of these variables: whether they belong to the model with the strongest external validation performance (TopAUC), the model with calibration closest to the ideal (BestCal), or an original model that explicitly used dynamic data (Dyn).

To ensure consistent judgment criteria, model attribution, performance attribution, and variable conflicts must all be based on the verifiable model descriptions, performance summaries, and field definitions in the target papers. When the same concept has multiple naming or mapping methods, prioritize conservative mappings that maintain cross-model interpretability consistency, and flag mapping differences that may affect interpretability consistency.

After completing the above literature tracing and variable characteristic extraction, finally extract these parameters to generate a formatted single-line summary record. For status flags, uniformly use 1 for yes and 0 for no for all boolean types. If the search fails to locate the one validation paper and the three original model papers, output NONE. If all are successfully located, after arranging all distinct variables strictly in alphabetical order by variable name, concatenate the parameters within each variable in the fixed order "variable~category~B~W~Zh~Zo~WHOfield~WHOx~TopAUC~BestCal~Dyn~Conflict", then join all variables with "|" into a single string with no spaces.

If the search fails to locate the one validation paper and the three original model papers, output NONE. If all are successfully located, after arranging all distinct variables strictly in alphabetical order by variable name, concatenate the parameters within each variable in the fixed order "variable~category~B~W~Zh~Zo~WHOfield~WHOx~TopAUC~BestCal~Dyn~Conflict", then join all variables with "|" into a single string with no spaces. For all boolean types, uniformly use 1 for yes and 0 for no.

First, in the 2024 WHO global individual patient data validation paper, identify the four prognostic models that were successfully externally validated in LMIC data, and trace back to the three corresponding original model papers.

For each predictor, retain the original wording from WHO Table 1, annotate its matching method (E/M) in the WHO baseline table, and indicate whether it comes from the TopAUC, BestCal, or Dyn model.

When encountering a predictor that was conceptually merged on the WHO side, trace back to the original Wang/Zhou papers to split it apart and then recalculate the relevant fields.

the 2024 WHO global validation paper yields the four externally validated models and the WHO-side predictor wording/mapping baseline

the three original model papers yield model-specific predictor wordings, dynamic-data flags, and conflicts hidden by WHO-side conceptual merging

final rows are produced only after WHO predictors are kept separate, traced back to the original papers, and then re-annotated for mapping and model provenance

conceptually merged WHO predictors must be split back out when the original Wang/Zhou papers expose distinct variables

Table 2 mapping decisions are not valid until Table 1 wording and original-paper predictor sets are reconciled

TopAUC / BestCal / Dyn flags must be determined after the predictor split is applied correctly

the 2024 WHO global IPD validation paper and the three linked original COVID prognosis-model papers, using their current open-access full texts and tables

Exclude results that directly merged conceptually similar predictors after WHO Table 1 without tracing back to the original papers for splitting.

Exclude results that relied solely on loose mapping from WHO Table 2 without incorporating the original paper wording.

Exclude results that fixed TopAUC/BestCal/Dyn annotations before applying the predictor split correction.

variable category B W Zh Zo WHOfield WHOx TopAUC BestCal Dyn Conflict

the candidate variable set comes only from the WHO validation Table 1 and remains at the original 20 predictors

do not pre-merge the three source conflict groups `Smoking`/`Smoking status`, `Chronic renal disease`/`Chronic kidney disease`, and `Coronary heart disease`/`Heart disease` before applying the conflict flag

B, W, Zh, Zo, TopAUC, BestCal, Dyn, and Conflict are emitted as 1 or 0 only

emit `E` for exact WHO matches or direct matches under a substantively equivalent name, `M` for the fixed mapped match, and `NA` when no WHO field matches


Instruction: I am compiling a reference list of medications for ulcerative colitis for in-hospital use. From the immunosuppressants cataloged in KEGG, I want to select those drug entries that have been approved in Japan by the end of June 2025 and that carry explicit CYP-related metabolism information or CYP inhibition indications. Please proceed in the following order: first, within the scope of KEGG immunosuppressants for ulcerative colitis, screen for drug entries approved in Japan by the end of June 2025; then check whether each entry has explicit CYP-related metabolism information or CYP inhibition indications, retaining only qualifying entries. Next, record each entry's Japanese therapeutic classification code, ATC code, corresponding target branch, and Japan first approval date. Finally, output a single-line string sorted by Japan first approval date from earliest to latest, in the format <DRUG_ID>|<JP_class>|<ATC>|<Target_branch>|<JP_date>; separate entries with commas; if no qualifying entries exist, output NONE.

Output a single-line string sorted by Japan first approval date from earliest to latest, in the format <DRUG_ID>|<JP_class>|<ATC>|<Target_branch>|<JP_date>; separate entries with commas; if no qualifying entries exist, output NONE.

Within the scope of KEGG immunosuppressants for ulcerative colitis, retain only entries approved in Japan by 2025-06-30 and that carry explicit CYP-related metabolism information or CYP inhibition indications.

Candidate drugs must be re-verified against the corrected UC drug list for Japanese therapeutic classification, ATC, target branch, CYP evidence, and Japan first approval date.

Finally, output sorted by Japan first approval date from earliest to latest.

KEGG disease H01466 and linked drug entries yield the ulcerative-colitis immunosuppressant candidate set

each candidate drug entry yields Japanese class, ATC, target branch, CYP metabolism/inhibition evidence, and Japan approval date

final rows are produced only after the full UC candidate set is determined and every candidate is checked against CYP evidence and PMDA timing

the candidate set must include Japanese class 3999 UC drugs when the disease page exposes them rather than being limited to 2399 alone

target / CYP / PMDA validation must be applied across the full candidate set rather than only the old 2399 subset

entries without explicit CYP evidence may be dropped only after the full candidate set has been established

KEGG ulcerative-colitis drug candidates with Japan approvals on or before 2025-06-30; current drug-entry annotations provide target, CYP, and Japan-class metadata

Exclude results that incorrectly lock the upstream scope to the 2399 digestive branch without falling back to the full UC drug list.

Exclude entries without explicit CYP-related metabolism information or CYP inhibition indications.

Exclude entries with a Japan approval date after 2025-06-30 or that are not within the KEGG UC immunosuppressant scope.

use the canonical KEGG-style date format YYYY/M/D with no zero-padding requirement beyond the source value

emit the most specific target branch visible in the source path; when multiple parallel branches survive, join them with `/`


Instruction: I am preparing a lecture page on classic animal endosymbiosis cases and want to find, among KEGG's host-symbiont examples, the case that meets the following conditions: it was already recorded by the end of 2005, its bacterial symbiont genome contains named extra replicons, and the names of those replicons directly correspond to amino acid synthesis modules on the host-symbiont joint pathway map. Process in the following order: first, among KEGG's host-symbiont examples, select those combinations whose bacterial symbiont KEGG GENOME entry has a Created year on or before 2005; then retain cases where the bacterial symbiont genome carries named extra replicons; next, verify that the replicon names directly correspond to amino acid synthesis modules on the host-symbiont joint pathway map; finally, within the joint pathway map for that host-symbiont combination, list all qualifying pathway-module pairs for that case and output a single-line string: <group>|<symbiont>|<pathway>|<module>|<replicon>|<created_year> (sorted by pathway ID in ascending order, separated by commas; output NONE if no qualifying items exist).

Output a single-line string: <group>|<symbiont>|<pathway>|<module>|<replicon>|<created_year> (sorted by pathway ID in ascending order, separated by commas; output NONE if no qualifying items exist).

Retain only those host-symbiont examples where the bacterial symbiont KEGG GENOME Created year is on or before 2005 and the genome carries named extra replicons.

The replicon names must directly correspond to amino acid synthesis modules on the host-symbiont joint pathway page.

Finally, output all qualifying pathway-module-replicon records from the surviving case, sorted by pathway ID in ascending order.

KEGG host-symbiont examples and symbiont genome pages yield the pre-2006 candidate pairs and named extra replicons

Joint pathway maps, module pages, and genome annotations yield the pathway-module-replicon links attributable to the symbiont side

Final rows are produced only after the surviving host-symbiont pair is validated against both replicon existence and module support on the joint pathway page

Only branches satisfying the named-plasmid requirement may be retained, so the bmy+wbm branch must be excluded when the wbm genome page fails that requirement

Module retrieval must use the api+buc pathway state and the 00400 view, because that view is the one that actually exposes M00023

Module support is valid only after symbiont-side evidence for both M00023 and M00432 is validated in the selected pathway state

KEGG host-symbiont examples whose symbiont GENOME Created year is on or before 2005; current joint pathway, module, and genome replicon annotations

Exclude cases like bmy+wbm where the symbiont genome page does not satisfy the named-plasmid requirement.

Exclude results that only follow pathway names along pages such as 00380 without returning to the joint pathway page to verify module evidence.

Exclude records where the relationship between replicon name and module cannot be directly established on the joint pathway map.

group symbiont pathway module replicon created_year

Use the canonical host-symbiont group label from the source workflow, such as `api+buc`

Use the bare lowercase KEGG organism code

Emit the numeric KEGG pathway ID without a `map` prefix

Normalize the KEGG module identifier to the `Mxxxxx` form

Preserve the named extra replicon exactly as displayed in the source, such as `pLeu` or `pTrp`


Instruction: I am compiling a table of the approval order of systemic drugs for plaque psoriasis in Japan. Process as follows: first, within the scope of systemic drugs for plaque psoriasis approved in Japan by the end of 2024, identify the active ingredients that act on the IL-17/IL-23 signaling axis; then exclude all topical drugs and systemic drugs acting on other axes. Next, sort these active ingredients by their first approval date in Japan from earliest to latest; if approved on the same day, sort by DRUG_ID in ascending order. Finally, output a multi-row table with each row formatted as <DRUG_ID>|<Name>|<ATC>|<Target_branch>|<PMDA_date>.

Output a multi-row table with each row formatted as <DRUG_ID>|<Name>|<ATC>|<Target_branch>|<PMDA_date>.

Retain only the active ingredients that truly act on the IL-17/IL-23 signaling axis among systemic drugs for plaque psoriasis approved in Japan by 2024-12-31.

The candidate set must cover the ligand side, receptor side, and TYK2 kinase side, not just the interleukin ligand side.

Sort final entries by Japan first approval date in ascending order; if on the same day, sort by DRUG_ID in ascending order.

KEGG disease/drug entry points yield the Japan-approved systemic plaque-psoriasis drug cohort through 2024-12-31

each drug entry yields target branch, ATC, systemic-use validity, and Japan approval date for IL-17/IL-23-axis candidates

final rows are produced only after ligand-side, receptor-side, and kinase-side candidates are jointly reconciled and re-sorted by Japan approval date

entry-point coverage must include receptor-side IL17RA and kinase-side TYK2 mechanisms when downstream drug pages expose them, rather than staying ligand-only

Ustekinumab must be removed only when target interpretation shows IL12 + IL23A rather than the IL-17/IL-23-axis criterion required here

systemic-use, Japanese 3999, and PMDA-date filtering must be applied after each expansion of the candidate set rather than attached to the earlier ligand-only state

Japanese plaque-psoriasis systemic drugs approved on or before 2024-12-31; current KEGG drug-entry annotations supply target branches and Japan approval dates

Exclude topical drugs, non-systemic drugs, or entries outside the specified historical freeze window.

Exclude entries such as Ustekinumab whose actual target is IL12 + IL23A and which do not meet the IL-17/IL-23 axis criterion required here.

Exclude results that miss Brodalumab or Deucravacitinib due to looking only at the ligand side.

omit the header row; emit data rows only

use the canonical KEGG-style date format YYYY/M/D with no zero-padding requirement beyond the source value


Instruction: I am preparing a handout for a primate evolution course and want to summarize, in a two-row comparison table, the anomalous pattern behind why this lineage must obtain vitamin C from the diet. Among primate genome entries established by the end of 2022, identify the anomalous lower-level clade in which the upstream glucuronate module M00014 is still retained but the animal-type vitamin C biosynthesis module M00129 has been lost. Then verify the corresponding sister branch and confirm that it still retains M00129. Finally, output a two-row comparison table with columns rank|clade_role|parent_clade|clade|anomaly_pathway|contrast_pathway|retained_upstream_module|vitamin_c_synthesis_module|vitamin_c_module_status|example_org|cutoff_year. The first row should be EXCEPTION_CLADE and the second row RETAINED_SISTER_CLADE. In all rows, vitamin_c_synthesis_module is fixed as M00129; vitamin_c_module_status should be LOST for the first row and RETAINED for the second. Use KEGG organism codes for the example species.

Output a two-row comparison table with columns rank|clade_role|parent_clade|clade|anomaly_pathway|contrast_pathway|retained_upstream_module|vitamin_c_synthesis_module|vitamin_c_module_status|example_org|cutoff_year.

Search only among primate genome entries established by the end of 2022, and isolate the anomalous lower-level clade that retains the upstream glucuronate module M00014 but lacks the animal-type vitamin C biosynthesis module M00129.

That anomalous clade must be paired with a sister branch under the same higher-level split, and the sister branch must still retain M00129.

The final output must place the anomalous branch and the retained sister branch into a two-row comparison table, including the required pathway, module, and example-species fields.

the KEGG primate clade pages and genome entries yield candidate subclades and example species established through the cutoff year

the pathway and module views yield M00014 and M00129 presence/absence evidence for the exception clade and its sister branch

final rows are produced only after the exception clade and retained sister branch are jointly validated under the same parent split and paired with example organisms

the exception clade remains provisional until both the sister-branch contrast and the example-species checks succeed

the comparison view must make retained M00014 and missing M00129 visible together

the two output rows are emitted together only after the exception clade and retained sister branch are fixed under the same parent split

primate genome entries established on or before 2022, with current KEGG clade, pathway, and module pages used as relatively stable reference information for comparing retained M00014 against lost M00129

That anomalous clade must have a contrastable sister branch, and that sister branch must still retain M00129.

Exclude results that stop at Simiiformes without checking the broader boundary and therefore miss Haplorrhini.

Exclude pathway views that do not make the M00014 versus M00129 contrast visible together.

Exclude candidate clades that have not been validated against a retained sister branch.

emit 1 for EXCEPTION_CLADE and 2 for RETAINED_SISTER_CLADE

emit KEGG pathway ids with the map prefix

use bare KEGG organism codes in lowercase, not species names

use a four-digit year; this task is frozen at 2022

emit rows in the fixed order EXCEPTION_CLADE then RETAINED_SISTER_CLADE


Instruction: We are cleaning up a batch of old SBOM matching rules for the Duplicator product line. Some rules still rely on legacy vendor lineage and outdated product labeling, so we need to identify Duplicator-related CVEs whose current product line belongs to awesomemotive:duplicator but can still be traced back to snapcreek:duplicator in the deprecated vendor chain. Search NVD records for Duplicator-related CVEs published from 2018-01-01 through 2024-12-31. Retain only CVEs that satisfy all of the following conditions in Change History: the Initial Analysis is not yet lite or lite+pro; the first change to lite or lite+pro occurs in a NIST analysis event on 2021-10-18; and a snapcreek -> awesomemotive vendor remap occurs on 2026-02-02. Exclude CVEs whose Initial Analysis already contained lite/lite+pro, as well as records that lack the required vendor-remap event or do not belong to the Duplicator product line. Finally, output a single-line ordered table with columns: CVE | lite_upper_version | lite_vs_lite+pro | analysis_event@date | snapcreek_to_awesomemotive@date.

Output a single-line ordered table with columns: CVE | lite_upper_version | lite_vs_lite+pro | analysis_event@date | snapcreek_to_awesomemotive@date. Join rows with commas and sort by NVD published date ascending, then by CVE ascending.

Retain only Duplicator-related CVEs whose current product line belongs to awesomemotive:duplicator and that can be traced back to snapcreek:duplicator in the deprecated old vendor chain.

Each candidate CVE must simultaneously satisfy the following in its Change History: the Initial Analysis is not yet lite/lite+pro; the first change to lite or lite+pro occurs in a NIST analysis event on 2021-10-18; and a snapcreek -> awesomemotive vendor remap occurs on 2026-02-02.

The final output retains only CVE rows that satisfy all three conditions above.

NVD product/CPE search pages yield the current awesomemotive:duplicator family and the deprecated snapcreek:duplicator lineage

each target CVE detail page and Change History yield the Initial Analysis state, the first lite/lite+pro analysis event, and the 2026-02-02 vendor-remap event

final rows are produced only after candidate CVEs are intersected on both snapcreek -> awesomemotive migration and later introduction of lite/lite+pro in NIST analysis history

the search must include the deprecated snapcreek lineage rather than only the current product state

vendor migration alone is insufficient until detail-level history confirms that lite/lite+pro was introduced after Initial Analysis

candidate CVEs must be filtered against the full change-history chronology, excluding any whose Initial Analysis already contained lite

Duplicator CVEs published from 2018-01-01 through 2024-12-31, evaluated against NVD analysis history up to the 2026-02-02 snapcreek -> awesomemotive vendor-remap events

Exclude results that only look at the current description or current product state without falling back to the deprecated snapcreek chain and Change History.

Exclude CVEs whose Initial Analysis was already lite/lite+pro.

Exclude records without a 2026-02-02 vendor remap, or that do not belong to the Duplicator product line.

the checked oracle rowset uses the Duplicator CVE schema below, and normalization follows that verified schema throughout this task

emit the identifier in the canonical `CVE:YYYY-NNNN` form used by the oracle

emit `Reanalysis@YYYY-MM-DD` or `ModifiedAnalysis@YYYY-MM-DD` exactly as supported by the source record

emit the ownership-transfer event as `snapcreek->awesomemotive@YYYY-MM-DD`


Instruction: Identify which CPE 2.3 product identifiers using the legacy vendor name mysql:mysql within the MySQL 5.1 branch were explicitly migrated by NIST to the corresponding oracle:mysql CPE 2.3 product identifiers in the NVD (National Vulnerability Database) records for the four InnoDB denial-of-service vulnerabilities CVE-2010-3676, CVE-2010-3677, CVE-2010-3678, and CVE-2010-3680. Migration here refers only to the vendor field in the CPE changing from the old vendor mysql to the new vendor oracle; it does not include cases where the identifier remains under the old vendor name and only version aliases are normalized. Retain only entries from the MySQL 5.1 branch that meet this criterion. Exclude entries from the MySQL 5.0 branch, as well as all entries that did not undergo a vendor migration and only had internal version-alias normalization under the old vendor. Output a multi-row ordered table with columns version_update | legacy_cpe | current_cpe | remap_time_nvd, sorted by numeric version in ascending order; within the same version, entries without an update suffix come before entries with an update suffix.

Retain only CPE 2.3 entries from the MySQL 5.1 branch for which the NVD Change History of all four vulnerabilities CVE-2010-3676, CVE-2010-3677, CVE-2010-3678, and CVE-2010-3680 clearly shows a mysql:mysql -> oracle:mysql vendor migration.

Every result must provide version_update, legacy_cpe, current_cpe, and remap_time_nvd.

Within the same version, entries without an update suffix come before entries with an update suffix, and output is sorted by numeric version in ascending order.

Current and deprecated MySQL 5.1 CPE search results yield candidate legacy/current CPE strings.

The four target CVE pages and their Change History entries yield vendor-migration evidence, exact version_update strings, and remap timestamps.

Final rows are produced only after taking the common mysql:mysql 5.1 -> oracle:mysql 5.1 migrations across all four CVEs and removing alias-only or 5.0 entries.

Legacy vendor mapping must be determined from Analysis Description plus Change History rather than from the current description/current CPE view.

Include-deprecated results cannot be accepted wholesale because alias-only remaps must be filtered out.

5.1-branch membership and sort order must be determined after the vendor-migration filter removes 5.0 and non-migration rows.

The MySQL 5.1 branches visible in CVE-2010-3676, CVE-2010-3677, CVE-2010-3678, and CVE-2010-3680, restricted to explicit mysql:mysql -> oracle:mysql vendor-migration events.

Exclude entries from the MySQL 5.0 branch.

Exclude entries that remain under the old vendor mysql:mysql, only have internal version-alias normalization, and did not undergo a vendor migration.

Exclude results that are read only from the current Oracle MySQL 5.1 CPE state without using legacy mapping and Change History.

required literal first row `version_update|legacy_cpe|current_cpe|remap_time_nvd`

sort by numeric MySQL version ascending; within the same base version, the empty update comes before any non-empty update suffix

preserve the exact legacy CPE 2.3 string

preserve the exact current CPE 2.3 string

emit the NVD remap timestamp in `YYYY-MM-DD HH:MM:SS` form


Instruction: We are cleaning up a batch of old SBOM matching rules that still represent Apache Tomcat 9.0.0 pre-release milestone versions using the legacy CPE form 9.0.0.Mx. We need to identify which milestone versions satisfy both of the following conditions: (1) they appear in the current NVD affected-product version ranges for the four historical vulnerabilities CVE-2016-5018, CVE-2016-6794, CVE-2016-6796, and CVE-2016-6797; and (2) the NVD change history shows that the CPE for these versions was remapped from the old short form (e.g., m1, m2) to the full form (e.g., milestone1, milestone2). Start from the Apache Tomcat 9.0.0 milestone versions, check each against the current NVD affected-product version ranges for these four CVEs, then examine the corresponding change history records. Retain only those milestone versions that satisfy both conditions. Exclude milestones that are included only because of other Tomcat 9.0.0 pre-release vulnerabilities, and do not include Tomcat 6, 7, 8, 8.5, or any non-Tomcat products. Finally, output an ordered multi-row table sorted by milestone number in ascending order, with columns: milestone | legacy_cpe | current_cpe | required_cves | remap_time_nvd.

Output as a Markdown multi-row table with fixed column names: milestone | legacy_cpe | current_cpe | required_cves | remap_time_nvd. Sort by milestone number in ascending order (M1, M2, ..., M9).

Retain only Apache Tomcat 9.0.0 milestone versions that appear in the current affected-product ranges for all four target CVEs: CVE-2016-5018, CVE-2016-6794, CVE-2016-6796, and CVE-2016-6797.

These versions must also have a CPE Deprecation Remap from mN to milestoneN visible in the NVD Change History.

Finally, output sorted by milestone number in ascending order, and the required_cves field must list these four specific CVEs.

the current milestoneN CPE search and detail pages yield the Tomcat milestone family and the legacy mN mapping anchors

the four target CVE pages and Change History entries yield the exact mN -> milestoneN deprecation remaps and the required-CVE intersection

final rows are produced only after taking the remaps common to all four target CVEs and sorting by numeric milestone

the candidate milestone set must be determined from the four-target-CVE intersection rather than from all prerelease Tomcat CVEs

later remapped milestones such as M10+ must be excluded by applying the specified four-CVE boundary

only explicit NVD CPE Deprecation Remap events from mN to milestoneN count, so generic Tomcat prerelease visibility cannot be accepted as evidence

the Tomcat 9.0.0 prerelease milestones jointly covered by CVE-2016-5018, CVE-2016-6794, CVE-2016-6796, and CVE-2016-6797, with remap evidence fixed to the 2023-12-08 11:41:18 NVD deprecation events

Exclude milestones that are included only because of other Tomcat 9.0.0 pre-release vulnerabilities, such as M10/M11 and later milestones.

Exclude Tomcat 6, 7, 8, 8.5, or any non-Tomcat products.

Exclude records that lack explicit NVD remap evidence and are only visible on the current milestone page.

required literal first row `milestone|legacy_cpe|current_cpe|required_cves|remap_time_nvd`

emit the canonical milestone label `M1` through `M9` and sort by the numeric suffix ascending

preserve the exact legacy CPE 2.3 string containing the short milestone token such as `m1`

preserve the exact current CPE 2.3 string containing the full milestone token such as `milestone1`


Instruction: I am compiling a name concordance for early museum specimens of Indian snakes recorded in George A. Boulenger's 1890 work *The Fauna of British India, Including Ceylon and Burma*. Proceed as follows: first, using this specimen set as the scope, look up each corresponding current species page in the Reptile Database and retain only entries that simultaneously satisfy the following conditions: the species has since been reassigned to a different genus; the page still retains BMNH type specimen information; and the type locality still corresponds to India. For each qualifying entry, identify from the names listed on that page the oldest binomial that is closest to the present but has not yet been updated to the current genus name. Then, search again using this full old name and determine whether the search result points to only this single record. Finally, output the results as a single line sorted alphabetically by current accepted name, in the format <accepted name>|<old label>|<UNIQUE/AMBIG>|<BMNH status>; separate entries with semicolons. If no qualifying entries exist, output NONE.

Output the results as a single line sorted alphabetically by current accepted name, in the format <accepted name>|<old label>|<UNIQUE/AMBIG>|<BMNH status>; separate entries with semicolons. If no qualifying entries exist, output NONE.

Argyrophis oatesii|Typhlops oatesii|UNIQUE|SYNTYPES;Dendrelaphis grandoculis|Ahaetulla grandoculis|UNIQUE|LECTOTYPE;Fowlea sanctijohannis|Xenochrophis sanctijohannis|UNIQUE|HOLOTYPE;Gerrhopilus beddomii|Typhlops beddomii|UNIQUE|SYNTYPES;Hebius khasiensis|Amphiesma khasiense|UNIQUE|LECTOTYPE;Hebius parallelus|Amphiesma parallelum|AMBIG|LECTOTYPE;Indotyphlops jerdoni|Typhlops jerdoni|UNIQUE|SYNTYPES;Myriopholis blanfordii|Leptotyphlops blanfordi|AMBIG|SYNTYPES

Candidates must come from the historical museum entries of Indian snakes in Boulenger 1890 *Fauna of British India*.

The current Reptile Database species page must simultaneously satisfy: the species has been reassigned to a different genus; the page still retains BMNH type specimen information; the type locality still corresponds to India.

On each qualifying page, select the oldest binomial that is closest to the present but has not yet been updated to the current genus name, then perform an exact back-search using this old name and label it UNIQUE or AMBIG.

the Boulenger 1890 historical sample and current accepted-species pages yield candidates that changed genus while retaining BMNH type data and India-compatible type locality

each accepted page yields the nearest pre-current-genus old label, the BMNH type status, and the historical/type-locality evidence anchoring the entity

final rows are produced only after the old-label exact back-search is evaluated for uniqueness without losing the original entity anchor

when an exact old-label back-search now hits multiple species, the original anchored entity must be kept and the uniqueness label must be set to AMBIG

once a candidate has passed the historical-cluster, genus-shift, BMNH, and India-locality gates, later old-label ambiguity can only rewrite the uniqueness field, not the entity itself

candidate anchoring must be preserved across the two-stage workflow so that old-label search noise does not redirect the accepted-species row

the George A. Boulenger 1890 British India sample, evaluated against current Reptile Database accepted pages, synonym labels, BMNH type data, and present type-locality text

Exclude entries where the current accepted name has not undergone a genus change, or where the page no longer retains BMNH type specimen information.

Exclude entries whose type locality does not correspond to India.

Do not discard candidates whose exact old-name back-search is non-unique; such candidates should be retained and labeled AMBIG.

accepted name
old label
UNIQUE/AMBIG
BMNH status

emit the current accepted binomial exactly as shown in the reconciled source

preserve the historical label exactly as used on the legacy branch

normalize the type-status field to uppercase labels such as HOLOTYPE, LECTOTYPE, or SYNTYPES


Instruction: I am compiling current name correspondences for early museum specimens of Southeast Asian Lygosoma. The old labels correspond to Riopa combinations attributed to Smith (1935/1937) in the Synonym section of each species page, but some of these old names now map to multiple current species under the current classification. Process as follows: first, within the current Lygosoma checklist, examine each current species page and locate these Smith (1935/1937) Riopa combinations in the Synonym section; then compare these old names, identify those that point to multiple current species, and list all involved current species. Next, for each qualifying current species, record the first-listed type specimen number, type category, and the region ultimately corresponding to the type locality on that page. Finally, output the results as a single line with entries sorted alphabetically by current accepted name, in the format <accepted>|<Smith-era Riopa label>|<first type code>|<type status>|<region>; separate entries with semicolons; if no qualifying entries exist, output NONE.

Output the results as a single line with entries sorted alphabetically by current accepted name, in the format <accepted>|<Smith-era Riopa label>|<first type code>|<type status>|<region>; separate entries with semicolons; if no qualifying entries exist, output NONE.

Lygosoma bampfyldei|Riopa bampfyldei|BMNH 1946.8.10.84|SYNTYPES|East Malaysia;Lygosoma peninsulare|Riopa bampfyldei|LSUHC 13857|HOLOTYPE|Peninsular Malaysia;Lygosoma schneideri|Riopa bampfyldei|NMBA 4743|HOLOTYPE|Indonesia

Retain only those accepted species that can be traced from the Smith 1937 old-name chain to a current Lygosoma record and for which the type accession, type status, and locality can be read on the current page.

For each accepted record, output the accepted name, the corresponding old label, the type accession, the type status, and the locality.

If the same exact old name is attached to multiple accepted species, retain them as separate chains.

the Smith 1937 old-name chain yields the three current Lygosoma accepted pages connected to Riopa bampfyldei / Lygosoma bampfyldei

each accepted page yields its own type accession, type status, and type locality needed to separate the homonymous old-name paths

final rows are produced only after the one-to-many old-name split is rebuilt and the three paths are re-anchored to their own type evidence

same-specific-epithet matching cannot establish a one-to-one mapping when the same Smith 1937 old name appears on multiple accepted pages

once literal old-name reuse is exposed, the workflow must keep the original parallel three-chain state rather than collapsing to a one-to-one mapping

type accession and locality evidence must be read separately for each chain rather than patched onto the first stopping page

the current Reptile Database accepted pages linked to the Smith 1937 old-name cluster around Riopa bampfyldei, using current type accessions, statuses, and localities

Exclude results that assume the same species based solely on the old name and current specific epithet being identical.

Exclude results that retain only the first chain after discovering the same exact old name on multiple accepted pages.

Exclude results that do not return to each accepted page to re-verify the type accession and locality.

accepted
Smith-era Riopa label
first type code
type status
region

emit the current accepted binomial exactly as shown in the reconciled source

preserve the Smith-era Riopa label exactly as used on the legacy branch

emit the first accession code that follows the selected type-status statement

normalize the type-status field to uppercase labels such as HOLOTYPE or SYNTYPES

emit the modern geographic region label from the source reconciliation, such as East Malaysia or Peninsular Malaysia


Instruction: I am organizing current-name cross-references for a batch of early museum catalog cards that were still filed under Mabuya or Mabuia around 1980, and need to map them into the current Eutropis checklist. Process as follows: first, examine each species page in the current Eutropis checklist one by one, and on each page identify the first synonym label that is both in Mabuya or Mabuia form and tagged with the 1980 citation year. Then, perform an exact name search using that 1980 old label, and retain only those species for which the back-search result points to more than one current Eutropis entry. For each qualifying entry, record its current accepted name, the 1980 old label, the qualifier annotation for that old label on the page, and the first type category and code listed on the current page. Finally, output a single line per entry in the format <accepted>|<1980 label>|<qualifier>|<type status>|<first type code>, sorted alphabetically by old label and, within the same old label, by accepted name. Join entries with semicolons. If no qualifying entries exist, output NONE.

Output a single line per entry in the format <accepted>|<1980 label>|<qualifier>|<type status>|<first type code>, sorted alphabetically by old label and, within the same old label, by accepted name. Join entries with semicolons. If no qualifying entries exist, output NONE.

Eutropis indeprensa|Mabuya indeprensa|NONE|HOLOTYPE|CAS 85664;Eutropis sahulinghangganan|Mabuya indeprensa|PART-MISID|HOLOTYPE|PNM 9867;Eutropis multifasciata|Mabuya multifasciata|NONE|NEOTYPE|MZB 11912;Eutropis multicarinata|Mabuya multicarinata|NONE|HOLOTYPE|BMNH 1946.8.15.13-15;Eutropis borealis|Mabuya multicarinata borealis|NONE|HOLOTYPE|CAS 15447;Eutropis islamaliit|Mabuya multicarinata borealis|PART-MISID|HOLOTYPE|PNM 9847;Eutropis caraga|Mabuya multicarinata multicarinata|PART-MISID|HOLOTYPE|PNM 9845;Eutropis palauensis|Mabuya multicarinata multicarinata|PART-BYIMPL|HOLOTYPE|CAS 248251;Eutropis dattaroyi|Mabuya rudis|PART|HOLOTYPE|ZSI 25118;Eutropis rudis|Mabuya rudis|NONE|LECTOTYPE|BMNH 1946.8.15.26

Retain only those current Eutropis accepted species for which the synonym block contains, scanning top-down, a first synonym label that begins with Mabuya or Mabuia and has the year 1980.

Then, perform an exact name search using that 1980 old label, and output the accepted name, old label, back-search qualifier, type status, and type specimen.

If the subsequent back-search reveals additional matching entries, revisit the earlier results and include them in the final output.

current Eutropis detail pages yield the first 1980-tagged Mabuya/Mabuia synonym label for each accepted species

exact back-search on that 1980 old label yields the present accepted page, type status, and type specimen needed for the output row

final rows are produced only after the 1980-specific old-label anchor is rebuilt and the accepted-species set is expanded when back-search evidence reveals omitted entries

the workflow must identify the first Mabuya/Mabuia label carrying the 1980 year rather than stopping at the first old label on the page

when old-label back-search reveals missing entries such as Eutropis dattaroyi, the accepted-species set must be expanded to include them rather than patched in place

accepted-page synonym parsing and back-search interpretation must stay coupled so that 1980 labels are not replaced by older but irrelevant names

current Reptile Database Eutropis pages, restricted to the first synonym label that is both Mabuya/Mabuia-form and tagged with the 1980 citation year

Exclude results that mistakenly treat the first old name on the page as the first 1980 old label.

Exclude results whose exact back-search on the 1980 old label points to only a single current Eutropis entry.

Exclude results that, when subsequent evidence reveals omitted entries, do not revisit the earlier results and rebuild the accepted-species set.

accepted
1980 label
qualifier
type status
first type code

preserve the 1980-era label exactly as used on the legacy branch

normalize to one of `NONE`, `PART`, `PART-MISID`, or `PART-BYIMPL`


Instruction: I am organizing a batch of early museum catalog cards for half-toed geckos that still use the old labels listed in the comments section of the Hemidactylus brookii species page. Process as follows: first examine the old labels listed in the comments section of the current Hemidactylus brookii species page, and select those that are no longer placed in Hemidactylus brookii and for which the database has clearly provided their current assignment. Then, for each qualifying label, determine the current species it should ultimately be assigned to; if merging from that label to the current species must pass through an intermediate old name, write that intermediate name, otherwise write DIRECT. At the same time, record the type status, type code, and the country of the type locality for that label itself. Finally, output a single line with entries sorted alphabetically by legacy label: <legacy label>|<accepted>|<bridge>|<type status>|<type code>|<country>; separate entries with semicolons; if no qualifying entries exist, output NONE.

Output a single line with entries sorted alphabetically by legacy label: <legacy label>|<accepted>|<bridge>|<type status>|<type code>|<country>; separate entries with semicolons; if no qualifying entries exist, output NONE.

Hemidactylus brooki leightoni|Hemidactylus angulatus|DIRECT|HOLOTYPE|BMNH 1946.8.25.65|Colombia;Hemidactylus brookii haitianus|Hemidactylus angulatus|DIRECT|LECTOTYPE|ZMH R22378|Haiti;Hemidactylus brookii parvimaculatus|Hemidactylus parvimaculatus|DIRECT|HOLOTYPE|NMSL No. RG. 15|Sri Lanka;Hemidactylus brookii subtriedroides|Hemidactylus murrayi|Hemidactylus tenkatei|LECTOTYPE|BMNH [subtriedroides] [tenkatei]|Myanmar;Hemidactylus gleadowi|Hemidactylus gleadowi|DIRECT|NEOTYPE|BMNH 1884.7.25.8|Pakistan;Hemidactylus tenkatei|Hemidactylus murrayi|DIRECT|LECTOTYPE|RMNH 4353|Indonesia

Each result must start from the old-label chain specified in the task and ultimately determine the accepted name, bridge status, type status, type accession, and locality from the current accepted page.

For the subtriedroides branch, continue along tenkatei to murrayi, output the final accepted name as Hemidactylus murrayi, and retain bridge=Hemidactylus tenkatei.

For branches such as haitianus and leightoni, read their own locality/type lines rather than borrowing header information from the wrong page.

The old-label chains from Hemidactylus angulatus and related names yield accepted pages, bridge names, and the type/locality lines for each path.

Comment, Types, and type-comment blocks yield the later evidence that tenkatei is further sunk into H. murrayi.

Final rows are produced only after each old-label path is re-anchored to its own locality/type line and the subtriedroides -> tenkatei -> murrayi bridge chain is completed.

Type data must be taken from the locality/type line belonging to the actual old-label branch rather than from the header block of the wrong accepted page.

Stopping at the intermediate tenkatei bridge is insufficient; the workflow must continue to the later murrayi evidence and rewrite both tenkatei and subtriedroides final accepted names.

Bridge labels remain useful, but final accepted names and type lines must be determined from the deeper synonym chain.

Current Reptile Database pages for the Hemidactylus angulatus / brookii / murrayi complex, using present locality, type, comment, and type-comment blocks.

Exclude results that follow the wrong page hierarchy and apply the Holotype/locality from the H. angulatus page header to other branches.

Exclude results that stop early on the subtriedroides -> tenkatei chain without continuing to read the murrayi evidence.

Exclude results that fail to align the locality/type line with each specific old-label branch.

legacy label
accepted
bridge
type status
type code
country

Preserve the legacy label exactly as used on the source branch.

Emit the current accepted binomial exactly as shown in the reconciled source.

Emit `DIRECT` when no intermediate legacy bridge name is needed; otherwise emit the intermediate legacy name that links the branches.

Normalize the type-status field to uppercase labels such as HOLOTYPE, LECTOTYPE, or NEOTYPE.

Take the type accession from the legacy-label branch rather than from a generic type line elsewhere on the page.

Emit the modern English country name from the reconciled source branch.


Instruction: I am checking a synonymization record in the current Naja species list that involves an early Sri Lankan museum name, and I want to organize the key information from the accepted side and the contested-name side into a two-row comparison table. First, in the current Naja list, locate the contested-name record associated with Sri Lanka. Then verify its recent-use evidence, the database's final treatment, the correction concerning lectotype assignment, the restricted type locality, and the holotype information for the contested name itself. Finally, output a two-row comparison table with columns rank|name_role|name|status_or_evidence|specimen_role|specimen_code|supporting_note. Row 1 should be ACCEPTED_NAME and give the accepted name, final status, valid lectotype, and restricted type locality. Row 2 should be CONTESTED_NAME and give the contested name, recent-use evidence, holotype, and the corrected invalid lectotype claim.

Output a two-row comparison table with columns rank|name_role|name|status_or_evidence|specimen_role|specimen_code|supporting_note.

1|ACCEPTED_NAME|Naja naja|SUBJECTIVE_JUNIOR_SYNONYM_OF_NAJA_NAJA|VALID_LECTOTYPE|ZMB 2796|restricted type locality: Sri Lanka
2|CONTESTED_NAME|Naja polyocellata|SHI et al. 2022+SILVA et al. 2023|HOLOTYPE|BMNH 1946.1.18.50|invalid lectotype claim: NRM (= NHR) Lin-90

Within the current Naja list, identify the Sri Lanka contested-name branch: the name was recently reused as a distinct valid name, but the database now explicitly merges it back into the accepted name.

On the current Naja naja page, read the recent-use evidence, final synonym status, lectotype correction, restricted type locality, and the holotype information for the contested name itself.

The final output must organize the ACCEPTED_NAME side and the CONTESTED_NAME side into a two-row comparison table.

the current Naja species list and the Naja naja page yield the Sri Lanka contested-name branch, recent-use citations, and the accepted-name context

comment, Types, and type-comment blocks yield the final synonym treatment plus the valid and invalid lectotype assignments and the contested-name holotype

final rows are produced only after the accepted-name side and the contested-name side are reconciled on the current Naja naja page

recent-use evidence for Naja polyocellata must be interpreted together with the current final synonym treatment shown on that page

lectotype status must be fixed from the combined Types and type-comment evidence rather than from a single provisional assignment

the accepted-name and contested-name rows are emitted together only after final status, type locality, and specimen roles are fixed

the objectively existing taxa in the Sri Lanka Naja branch, using current Reptile Database comment, Types, and type-comment blocks as nearly objective and highly stable reference information

Within the current Naja list, identify the Sri Lanka contested-name record: the name was recently reused in the literature as a distinct valid name, but the database now explicitly states that it should still be merged into the accepted name.

On the current Naja naja page, the result must jointly recover the recent-use evidence, final synonym status, lectotype correction, restricted type locality, and the holotype information for the contested name itself.

Exclude results that treat the recently revived contested name as the current accepted name.

Exclude results that stop at the Wallach 2014 lectotype designation and do not continue to the later comment and type-comment correction.

Exclude results that fail to output both the restricted type locality and the contested-name holotype.

emit 1 for ACCEPTED_NAME and 2 for CONTESTED_NAME

use the current binomial spellings exactly

preserve museum abbreviations, spaces, parentheses, and specimen punctuation exactly as the page shows

emit rows in the fixed order ACCEPTED_NAME then CONTESTED_NAME


Instruction: I am compiling historical daily flow comparison data for the Saint John River spring freshet period and want to determine, along the mainstem, which station in the current monitoring network is the last one that still allows daily flow comparisons for March–April 1973 and March–April 2018, and which mainstem station downstream of it is the first one that no longer satisfies that condition. First, use the current monitoring network shown on the Wateroffice real-time page as of April 16, 2026, and retain only stations on the Saint John River mainstem. Then, for each station, check the historical availability page, distinguish Flow Data Availability from Daily Water Level Data Availability, and determine whether March–April 1973 and March–April 2018 both have complete daily flow records. If the target windows satisfy the complete daily flow condition, set target_window_status to PASS and final_verdict to KEEP. If the target years have only water level records and no daily flow records, set target_window_status to LEVEL_ONLY and final_verdict to REJECT. If daily flow records exist but any target month in March–April 1973 or March–April 2018 is missing or incomplete, set target_window_status to FLOW_GAP and final_verdict to REJECT. Finally, output a two-row breakpoint table with columns rank|station_number|breakpoint_role|target_window_status|final_verdict. In the first row, give the last usable station and set breakpoint_role to LAST_USABLE. In the second row, give the first failing station encountered downstream and set breakpoint_role to FIRST_DOWNSTREAM_FAIL.

Output a two-row breakpoint table with columns rank|station_number|breakpoint_role|target_window_status|final_verdict.

Determine the last station still usable for the target historical-window comparison only within the Saint John River mainstem stations in the current monitoring network.

On the historical availability page, Flow Data Availability must be distinguished from Daily Water Level Data Availability, and completeness for March–April 1973 and March–April 2018 must be checked.

The final output must provide both breakpoint rows, LAST_USABLE and FIRST_DOWNSTREAM_FAIL, under the same validation rule.

the current Saint John River mainstem station sequence provides the downstream order in which the breakpoints must be checked

per-station historical availability pages yield Flow Data Availability, Daily Water Level Data Availability, and target-month completeness for 1973 and 2018

the final breakpoint rows are produced only after the availability-page checks identify the last usable station and the first downstream failure under the same rule

the breakpoint pair must be determined from historical availability that distinguishes flow from level-only evidence

target-year/month completeness must be checked on the availability page rather than inferred from the station list

the second row is emitted only after the first downstream failing mainstem station is fixed under the same validation rule

mainstem candidate stations evaluated by historical daily availability, with the target completeness rule applied to the specified 1973 and 2018 March/April windows

Search for the final station only within the mainstem station set specified in the task, and continue downstream along the mainstem to identify the first station after it that no longer meets the condition.

The historical daily availability page must distinguish Flow Data Availability from Daily Water Level Data Availability, and must verify the completeness of the required March–April windows for 1973 and 2018.

Exclude results that rely only on the current Saint John River mainstem station sequence and directly take the most downstream station by reference index.

Exclude results that mistakenly treat level-only evidence as satisfying the flow condition.

Exclude results that do not check each station's availability page to verify target-month completeness.

emit `1` for LAST_USABLE and `2` for FIRST_DOWNSTREAM_FAIL

emit `LAST_USABLE` and `FIRST_DOWNSTREAM_FAIL` exactly

emit `PASS`, `LEVEL_ONLY`, or `FLOW_GAP` exactly

emit `KEEP` for the usable breakpoint row and `REJECT` for the downstream failing breakpoint row

the last usable mainstem station is fixed under the availability-page validation rule

the first downstream failing mainstem station is fixed under the same validation rule before the two-row output is emitted


Instruction: I am compiling historical daily flow records for the Bulkley River reach from Houston to Hazelton and want to verify, station by station, whether candidate mainstem stations on the Bulkley River truly have complete daily flow records for April–July 1948 and April–July 1950. First, from the Historical Results list, select candidate stations that lie on the Bulkley River mainstem, fall within the Houston-to-Hazelton reach, appear to cover both 1948 and 1950, and carry a Flow label. Then open each station's availability page and check whether the target years fall within the Flow section and whether April-July is marked C throughout. If the target windows satisfy the complete daily flow condition, set target_window_status to PASS and final_verdict to KEEP. If the target years have only water level records and no daily flow records, set target_window_status to LEVEL_ONLY and final_verdict to REJECT. If daily flow records exist but any month from April to July is not complete, set target_window_status to FLOW_GAP and final_verdict to REJECT. Finally, output a table in downstream-to-upstream order with columns rank|station_number|target_window_status|final_verdict.

Output a table in downstream-to-upstream order with columns rank|station_number|target_window_status|final_verdict.

1|08EE004|PASS|KEEP
2|08EE001|LEVEL_ONLY|REJECT
3|08EE005|FLOW_GAP|REJECT
4|08EE003|FLOW_GAP|REJECT

First identify mainstem candidate stations on the Historical Results list that appear to cover 1948/1950 and carry a Flow label.

A station qualifies only if its availability page shows the target years in the Flow section and all of April-July marked C.

The final output must report target_window_status and final_verdict for each station in the same station set, ordered from downstream to upstream.

the Historical Results list yields four downstream-to-upstream mainstem candidates whose result rows span the target years and include Flow labels

each candidate's availability page yields whether the target years are in the Flow table and whether April-July is complete

the final ordered rows are produced only after all four stations are classified under the full Flow-table-and-Apr-Jul-C rule

list-level year spans and coarse Flow tags must be confirmed by explicit target-month checks on the availability page

Hazelton, Smithers, and Houston candidate statuses must be fixed before the downstream-most KEEP row can be confirmed

row order and KEEP/REJECT labels must be emitted only after the full availability-page rule is applied to all four stations

the target mainstem stations tested against 1948 and 1950 daily Flow availability, with April-July requiring complete C coverage

First, from the Historical Results list, identify mainstem candidate stations that superficially appear to cover 1948/1950 and have a Flow label.

A truly qualified station must satisfy, on its availability page, that the target years are in the Flow section and that April–July are all marked C.

Finally, report target_window_status and final_verdict for each station in the same station set, ordered from downstream to upstream.

Exclude stations deemed usable based solely on list-level year span and coarse Flow label.

Exclude retaining LEVEL_ONLY or FLOW_GAP stations in the final answer.

Exclude results that do not apply the full availability-page rule to all initially screened stations.

emit 1 through 4 in downstream-to-upstream order within the validated station set

downstream to upstream within the validated Bulkley River mainstem station set

all four initially screened stations are classified under the full availability-page rule

the ordered table is emitted only after the downstream-to-upstream sequence is fixed


Instruction: I am compiling historical snowmelt daily flow data for the Thompson River from Chase to Spences Bridge. I need to verify, station by station, whether the mainstem stations along this reach actually have daily flow records for May–July of 1958 and 1971. First, in downstream order from Chase to Spences Bridge, select stations from the list that show coverage for 1958 and 1971 and have flow records for the Thompson River mainstem. Then, for each selected station, check whether it provides complete daily flow records for May–July of both 1958 and 1971. If a station has only water level records (no daily flow) for a target year, mark it LEVEL_ONLY. If daily flow records exist but the May–July window is missing or any target month is incomplete, mark it FLOW_GAP. Only when both years' May–July daily flow records are complete should the final_verdict be KEEP; otherwise, REJECT. Finally, output a table with columns rank|station_number|station_name|1958_MayJul|1971_MayJul|final_verdict, ordered downstream from Chase to Spences Bridge.

Output a table with columns rank|station_number|station_name|1958_MayJul|1971_MayJul|final_verdict, ordered downstream from Chase to Spences Bridge.

1|08LE031|SOUTH THOMPSON RIVER AT CHASE|PASS|PASS|KEEP
2|08LE069|SOUTH THOMPSON RIVER AT MONTE CREEK|FLOW_GAP|LEVEL_ONLY|REJECT
3|08LF023|THOMPSON RIVER AT KAMLOOPS|LEVEL_ONLY|LEVEL_ONLY|REJECT
4|08LF033|THOMPSON RIVER NEAR SAVONA|FLOW_GAP|FLOW_GAP|REJECT
5|08LF051|THOMPSON RIVER NEAR SPENCES BRIDGE|PASS|PASS|KEEP

All five candidate stations must be verified on the availability page to confirm that the target years are present in the Flow table and that May–July is entirely marked C.

Each station must output a PASS / LEVEL_ONLY / FLOW_GAP judgment for both target years, and then be marked KEEP or REJECT accordingly.

The result order must follow the river-path ordering specified in the task.

the river-path ordering yields five South Thompson / Thompson mainstem candidates

each station's availability page yields whether 1958 and 1971 are present in the Flow table and whether May-July is complete

final rows are produced only after every candidate is classified under the stricter target-year and target-month Flow rule

overall year coverage on the results list must be confirmed by the availability page inside the Flow table

Monte Creek, Savona, and Kamloops must be rejected by LEVEL_ONLY / FLOW_GAP evidence before the KEEP rows are final

the river-order sequence remains fixed, but station statuses must be assigned only after the availability-page rule is applied to all five stations

the ordered South Thompson / Thompson mainstem candidates tested against 1958 and 1971 Flow availability, with May-July requiring complete C coverage

Exclude results that treat overall year coverage on the list as sufficient evidence.

Exclude results that fail to distinguish between Flow table target-year and month completeness versus Level-only evidence.

Exclude results that do not apply the same availability-page rule uniformly to all five stations.

use the fixed Chase-to-Spences-Bridge mainstem order from the reference index, not the transient search-result order

the two year-window fields emit only PASS, LEVEL_ONLY, or FLOW_GAP


Instruction: I am compiling historical daily flow records for the mainstem Columbia River from Fairmont Hot Springs to the International Boundary. I want to check, station by station in Wateroffice, which stations have complete daily flow records for May–October of 1955 and 1956. First, locate stations on the Columbia River mainstem between Fairmont Hot Springs and the International Boundary whose records span both 1955 and 1956. Then, proceeding from upstream to downstream, check the availability of daily flow for May–October of 1955 and 1956 at each station. If a station has only water-level records and no daily flow records for a given target year, mark that year as LEVEL_ONLY. If daily flow for May–October of that year is complete, mark it as PASS. Otherwise, if the year has no usable daily flow records or any month within May–October is incomplete, mark it as FLOW_GAP. Only when both years satisfy the PASS condition should the final_verdict be KEEP; otherwise write REJECT. Finally, output a table in upstream-to-downstream order with columns: rank|station_number|station_name|1955_MayOct|1956_MayOct|final_verdict.

Output a table in upstream-to-downstream order with columns: rank|station_number|station_name|1955_MayOct|1956_MayOct|final_verdict.

1|08NA045|COLUMBIA RIVER NEAR FAIRMONT HOT SPRINGS|PASS|PASS|KEEP
2|08NA004|COLUMBIA RIVER AT ATHALMER|LEVEL_ONLY|LEVEL_ONLY|REJECT
3|08NA052|COLUMBIA RIVER NEAR EDGEWATER|PASS|FLOW_GAP|REJECT
4|08NA002|COLUMBIA RIVER AT NICHOLSON|PASS|PASS|KEEP
5|08NB005|COLUMBIA RIVER AT DONALD|PASS|PASS|KEEP
6|08NB006|COLUMBIA RIVER AT SURPRISE RAPIDS|PASS|PASS|KEEP
7|08ND007|COLUMBIA RIVER ABOVE NAGLE CREEK|PASS|PASS|KEEP
8|08ND011|COLUMBIA RIVER ABOVE STEAMBOAT RAPIDS|FLOW_GAP|PASS|REJECT
9|08ND006|COLUMBIA RIVER AT TWELVE MILE FERRY|PASS|PASS|KEEP
10|08NE002|COLUMBIA RIVER AT CASTLEGAR|LEVEL_ONLY|LEVEL_ONLY|REJECT
11|08NE049|COLUMBIA RIVER AT BIRCHBANK|PASS|PASS|KEEP
12|08NE003|COLUMBIA RIVER AT TRAIL|LEVEL_ONLY|LEVEL_ONLY|REJECT
13|08NE058|COLUMBIA RIVER AT INTERNATIONAL BOUNDARY|PASS|PASS|KEEP

Every candidate Columbia River station must be checked on its availability page to confirm that the target years appear in the Flow table and that May–October is fully marked C.

For each station, provide the KEEP/REJECT basis for both 1955 and 1956, distinguishing LEVEL_ONLY and FLOW_GAP cases from stations that only appear eligible from their overall year span.

The final table must preserve the order and fields specified in the task.

the Columbia River candidate ordering yields fourteen stations spanning the target years

each availability page yields whether 1955 and 1956 are present in the Flow table and whether May-October is complete

final rows are produced only after every station is classified under the stricter Flow-table-and-May-Oct-C rule

list-level year spans must be confirmed by the availability page inside the Flow table

LEVEL_ONLY and FLOW_GAP evidence must be applied to each station before the KEEP/REJECT table is finalized

station-by-station verdicts and rejection reasons must be determined only after the full availability-page rule replaces the initial year-span screen

the ordered Columbia River candidates tested against 1955 and 1956 Flow availability, with May-October requiring complete C coverage

Exclude results that retain a station solely because its overall record spans 1955/1956.

Exclude results that fail to distinguish, station by station, between Flow availability, Level-only, and incomplete months.

Exclude results that do not apply the full availability-page rule uniformly to all 14 stations.

use the fixed upstream-to-downstream Columbia mainstem order from the reference index, not the transient search-result order


Instruction: I am organizing historical daily-flow records for the Peace River reach from Dunvegan Bridge to Fifth Meridian and want to verify three things at once: the true furthest-downstream reusable station on the mainstem, the first failing station encountered after it, and the provisional terminal station that a station-level screen based only on year coverage and record type would mistakenly treat as the downstream winner. Screen only among Peace River mainstem stations between Dunvegan Bridge and Fifth Meridian. First, from the station list, identify provisional candidates that appear to cover both 1966 and 1967 and show a daily-flow record type. Then open each availability page and verify whether May through September in both 1966 and 1967 appears in the Flow table and is complete for every month. If both target years satisfy the complete daily-flow condition, write PASS in target_window_status. If a target year has only level records and no daily-flow records, write LEVEL_ONLY. If daily-flow records exist but any target month from May through September is incomplete, write FLOW_GAP. If the target year has neither daily-flow nor level records, write NO_TARGET_RECORD. Finally, output a three-row diagnostic table with columns rank|station_number|diagnosis_role|target_window_status|provisional_count|final_count. The rows must be FINAL_STATION, FIRST_BREAK_AFTER_FINAL, and PROVISIONAL_STATION in that order, and the last two columns must repeat the global provisional_count and final_count in every row.

Output a three-row diagnostic table with columns rank|station_number|diagnosis_role|target_window_status|provisional_count|final_count.

A genuinely reusable station must satisfy the availability-page rule that both 1966 and 1967 appear in the Flow table and that every month from May through September is complete.

The final output must jointly report FINAL_STATION, FIRST_BREAK_AFTER_FINAL, and PROVISIONAL_STATION, while repeating provisional_count and final_count in every row.

the Peace River mainstem chain between Dunvegan Bridge and Fifth Meridian yields the initial station list and the downstream breakpoint positions that need revalidation

each availability page yields whether 1966 and 1967 are present in the Flow or Level tables and whether May-September is complete

final rows are produced only after the final station, the first downstream failure, and the provisional downstream winner are all fixed under the same availability-page validation rule

station-level target-year Flow evidence must be validated by explicit May-September completeness checks on the availability page

the final downstream reusable station and the first downstream failure must be determined under the same validation rule rather than from the initial station screen

the provisional downstream winner is kept in the output only for reference after its FLOW_GAP status is confirmed on the availability page

Peace River mainstem stations between Dunvegan Bridge and Fifth Meridian, evaluated within the fixed historical 1966 and 1967 Flow-availability windows, with May-September complete-C coverage used as nearly stable reference information

Exclude results that treat a station as usable simply because the target years have Flow records.

Exclude results that do not verify completeness month by month from May through September.

Exclude results that mark a station such as 07KA002 as FINAL_STATION when availability-page evidence shows FLOW_GAP.

emit the fixed order 1, 2, 3 for FINAL_STATION, FIRST_BREAK_AFTER_FINAL, and PROVISIONAL_STATION

use uppercase WSC station codes exactly as the Reference Index and availability pages show

repeat the global provisional_count and final_count in every row as plain integers

emit rows in the fixed diagnostic order FINAL_STATION, FIRST_BREAK_AFTER_FINAL, PROVISIONAL_STATION


Instruction: I am reviewing historical monitoring records for a reach of the middle Rio Grande and need to select two monitoring stations suitable for observing wastewater impacts on the main channel. Starting from RIO GRANDE AT EMBUDO, NM and proceeding downstream, retain only stations that are confirmed to lie on the Rio Grande mainstem. Then, find the first mainstem monitoring station downstream of the Town of Bernalillo wastewater treatment plant outfall that meets the following conditions; continuing further downstream, find the first mainstem monitoring station that has passed both the Town of Bernalillo WWTP outfall and the Rio Rancho No. 2 WWTP outfall and meets the same conditions. Both stations must satisfy: the station itself is not an outfall, facility, well, canal, or drainage ditch; the type on the station detail page is labeled as River/Stream; records for the four characteristic groups Microbiological, Nutrient, Organics, Other, and Physical fully cover 2015–2020; and the start years for both Microbiological and Physical records are earlier than 2010. Finally, output a single-line string in upstream-to-downstream order: <mainstem station ID>|<Microbiological start year>|<Physical start year>, with the two segments separated by a comma.

Output a single-line string in upstream-to-downstream order: <mainstem station ID>|<Microbiological start year>|<Physical start year>, with the two segments separated by a comma.

Select two target stations only from Rio Grande mainstem monitoring stations downstream of RIO GRANDE AT EMBUDO, NM, and both must have passed the specified outfall locations.

The station detail page must explicitly show River/Stream, and records for the four characteristic groups Microbiological, Nutrient, Organics, Other, and Physical must fully cover 2015–2020, while the start years for both Microbiological and Physical must be earlier than 2010.

Output the two final stations in upstream-to-downstream order.

provider/list views yield the Rio Grande mainstem candidates downstream of the Bernalillo and Rio Rancho No. 2 discharge points

detail pages yield flow position, location type, characteristic-group period-of-record coverage for 2015-2020, and the Microbiological/Physical baseline years

final rows are produced only after the corrected downstream sentry stations are fixed and ordered from upstream to downstream

provider-list stream tags are only provisional and must be confirmed on the detail page by both mainstem placement and location type

target-window presence is insufficient until full 2015-2020 coverage is confirmed on the detail page for all four groups

once RG002/RG007 fail the full detail-page checks, the workflow must continue downstream from the discharge-point starting position to RG003/RG008

Rio Grande mainstem stations downstream of the Town of Bernalillo and Rio Rancho No. 2 WWTP outfalls, validated against 2015-2020 coverage for Microbiological, Nutrient, Organics, Other, and Physical

Exclude stations that have only a superficial (Stream) tag on the provider list or have records near the target window, but whose detail page does not satisfy the flow position, location type, or complete period-of-record conditions.

Exclude locations that are outfalls, facilities, wells, canals, or drainage ditches.

Exclude candidates such as RG002 and RG007 that are not the qualifying sentry stations downstream of the corresponding outfalls.

emit exactly two records from upstream to downstream

the first qualifying mainstem station below the Bernalillo outfall

the first qualifying mainstem station below both the Bernalillo and Rio Rancho No. 2 outfalls

the Bernalillo branch stops only after its first qualifying mainstem station is fixed

the Rio Rancho No. 2 branch stops only after its first qualifying mainstem station is fixed

the two segments are emitted as one comma-joined line in upstream-to-downstream order


Instruction: I am analyzing trends in the lower Rio Grande from 2001 to 2010. From monitoring stations located below RIO GRANDE BELOW ANZALDUAS and still within HUC 13090002, select one representative station for Hidalgo County and one for Cameron County. First, screen candidate stations for each county within the specified area. Retain only stations whose detail page lists the type as River/Stream and that have records covering 2001–2010 for all four characteristic groups: Microbiological, Nutrient, Organics, Other, and Physical. If multiple stations in the same county qualify, select the station with the earliest year in which all four groups are simultaneously present. Then record the MonitoringLocationIdentifier of the selected station, the earliest year all four groups are simultaneously present, and the start year for each of Microbiological, Nutrient, Organics, Other, and Physical. Finally, output a single-line string in the order Hidalgo then Cameron: <County>:<MonitoringLocationIdentifier>|<common_start_year>|<Microbiological_start_year>|<Nutrient_start_year>|<Organics_Other_start_year>|<Physical_start_year>, with the two segments separated by a comma.

Output a single-line string in the order Hidalgo then Cameron: <County>:<MonitoringLocationIdentifier>|<common_start_year>|<Microbiological_start_year>|<Nutrient_start_year>|<Organics_Other_start_year>|<Physical_start_year>, with the two segments separated by a comma.

Select one representative station for Hidalgo County and one for Cameron County from monitoring stations located below RIO GRANDE BELOW ANZALDUAS and still within HUC 13090002.

Candidate detail pages must list the type as River/Stream, and records for all four characteristic groups (Microbiological, Nutrient, Organics, Other, Physical) must cover 2001–2010.

the fixed downstream starting point and county split yield Hidalgo and Cameron candidate mainstem stations within HUC 13090002

detail pages yield River/Stream validity, the four characteristic-group start years, and the earliest year when all four groups are simultaneously present for 2001-2010 coverage

final rows are produced only after the county-specific searches are rerun from the fixed downstream starting point and then ranked by common-start year

the Hidalgo search must preserve the "below TCEQMAIN-13664" downstream starting point rather than returning to the anchor station itself

a station is only provisional until all four characteristic groups are confirmed for the same MonitoringLocationIdentifier and tidal/intake conflicts are excluded on the detail page

county winners are valid only after late-start and non-river candidates are removed and the common-start-year tie-break is recomputed

stations below RIO GRANDE BELOW ANZALDUAS within HUC 13090002, split by Hidalgo and Cameron County, with Microbiological, Nutrient, Organics, Other, and Physical coverage over 2001-2010

Exclude results where the Hidalgo search loses the downstream starting point and brings the starting station itself back into the candidate set.

Exclude results that treat a single multi-select of the four characteristic groups as sufficient without verifying that all four belong to the same station ID.

Exclude stations with tidal, intake, late-start, or other conflicts clearly indicated on the detail page.

emit exactly two records, with Hidalgo first and Cameron second

use the county label in title case, followed by : and the uppercase MonitoringLocationIdentifier

the earliest year in which all four required groups are simultaneously present for the chosen county station

each county branch is rerun until one River/Stream station survives all four group checks

the county winner is fixed only after late-start and non-river candidates are excluded after checking the detail page

the two county segments are emitted on one line in the fixed Hidalgo-then-Cameron order


Instruction: I am compiling 2012–2018 water quality reference data for the Brazos River mainstem downstream of Brazos Rv at Waco, TX. I want to select one TCEQ monitoring station suitable as a long-term reference point in each of the three HUCs (12060202, 12070101, 12070104) that the mainstem passes through. Process as follows: first, within the Brazos River mainstem reach downstream of Brazos Rv at Waco, TX, screen candidate stations in HUCs 12060202, 12070101, and 12070104 respectively; retain only monitoring locations whose detail page labels them as River/Stream and whose station name still corresponds to the Brazos River mainstem rather than another named waterbody. Next, check the record categories for these stations, retaining only those that cover 2012–2018 for all five categories: Inorganics, Major, Non-metals; Microbiological; Nutrient; Organics, Other; and Physical. Specifically, the station start year must be no later than 2012 and the end year no earlier than 2018. Finally, list the 3 results in order from upstream to downstream, each row formatted as: <HUC>|<MonitoringLocationIdentifier>|<earliest year when all five categories are jointly available>|<Inorganics, Major, Non-metals start year>|<Microbiological start year>|<Nutrient start year>|<Organics, Other start year>|<Physical start year>.

List the 3 results in order from upstream to downstream, each row formatted as: <HUC>|<MonitoringLocationIdentifier>|<earliest year when all five categories are jointly available>|<Inorganics, Major, Non-metals start year>|<Microbiological start year>|<Nutrient start year>|<Organics, Other start year>|<Physical start year>.

The search must stay anchored downstream of Waco and look for Brazos mainstem monitoring stations within the three HUCs specified in the task.

Each candidate station must be checked separately across the five characteristic groups and then matched back to the same station ID, after which the detail page must verify full 2012–2018 coverage and mainstem semantics.

For each HUC, retain only the qualifying station with the earliest common start year, and output the start-year fields required by the task.

the fixed downstream starting point below Waco and the three target HUC searches yield the Brazos mainstem candidate stations

detail pages yield true downstream position, mainstem-vs-tributary semantics, and five-group period-of-record coverage across 2012-2018

final rows are produced only after the three HUC-specific searches are carried out, matched by station ID, and ranked by the earliest year when all five groups are jointly available

the workflow must stay anchored downstream of Waco rather than reintroducing upstream stations such as TCEQMAIN-12044

name-based waterbody matches must be validated on the detail page by excluding tributaries such as LITTLE BRAZOS RIVER and confirming full-window coverage

station ranking must be determined after false positives from partial-window records are removed

Brazos River mainstem stations downstream of the Waco anchor, split across HUC 12060202, 12070101, and 12070104, with five characteristic groups covering 2012-2018

Exclude results that lose the downstream starting point below Waco and bring upstream stations back into the candidate set.

Exclude results that mistake tributaries such as LITTLE BRAZOS RIVER for the Brazos mainstem.

Exclude stations that have data near the query window but do not cover the entire 2012–2018 window.

preserve the HUC exactly as emitted in the source result

preserve the monitoring-location identifier exactly, for example `TCEQMAIN-12037`

emit the maximum of the five per-group start years

only keep mainstem river/stream sites whose five required groups all cover the target 2012-2018 window

upstream to downstream along the mainstem


Instruction:
I am reviewing toxic-pollutant-related water quality monitoring data for 1993–2001 along the Trinity River mainstem, bounded upstream by the reach near FM 85 and downstream by the reach near Interstate 10. I need to select one TCEQ long-term reference station for each of the upper, middle, and lower segments.

Starting from the Trinity River mainstem between the reach near FM 85 and the reach near Interstate 10, screen candidate monitoring locations in the upper, middle, and lower segments. Retain only stations whose record is tagged as River/Stream and whose name still refers to the Trinity River mainstem, not to other named water bodies or distributaries. Then check the record categories for these stations; keep only those that have all six record categories covering 1993–2001 (i.e., the start year is no later than 1993 and the end year is no earlier than 2001). Output the results from upstream to downstream.

Finally, list three rows from upstream to downstream along the river, each in the format: <HUC>|<MonitoringLocationIdentifier>|<earliest year with all six categories>|<Inorganics, Major, Non-metals start year>|<Microbiological start year>|<Nutrient start year>|<Organics, Other start year>|<Organics, PCBs start year>|<Physical start year>.

List three rows from upstream to downstream along the river, each in the format: <HUC>|<MonitoringLocationIdentifier>|<earliest year with all six categories>|<Inorganics, Major, Non-metals start year>|<Microbiological start year>|<Nutrient start year>|<Organics, Other start year>|<Organics, PCBs start year>|<Physical start year>.

Screen only among candidate stations where Trinity River mainstem semantics hold, and require all six characteristic groups to cover 1993–2001.

The six groups must be searched separately and then matched back to the same station ID, after which the detail page must verify full-window coverage and legacy toxics group completeness.

For each target segment, retain only the station that meets all group requirements and has the best common start year.

Trinity River mainstem candidate stations are generated from the target HUC searches and the six characteristic-group searches

detail pages yield River/Stream validity, 1993–2001 full-window coverage, and the group-specific start years needed for ranking

final rows are produced only after all six groups have been matched by station ID and detail-page validation removes partial-group and non-mainstem false positives

each of the six characteristic groups must be evaluated separately and confirmed against the same station ID before a multi-select result can be retained

station names and River/Stream tags are insufficient until the detail page confirms Trinity mainstem semantics and 1993–2001 full-window coverage

candidate rejection and final ranking must be determined after applying the PCBs / Organics, Other gap checks

Trinity River mainstem stations validated against six characteristic groups over 1993–2001, with ranking based on the earliest joint availability and group start years

Exclude results that mistakenly treat a single multi-select of characteristic groups as sufficient to satisfy the requirement.

Exclude results that only check station names and River/Stream tags without verifying 1993–2001 full-window coverage.

Exclude stations that ignore missing PCBs or Organics, Other groups.

preserve the monitoring-location identifier exactly, for example `TCEQMAIN-10924`

emit the maximum of the six per-group start years

only keep mainstem river/stream sites whose six required groups all cover the target window