| --- |
| license: mit |
| language: |
| - en |
| pretty_name: ABX-PD-009 Inoculum Effect Coherence |
| tags: |
| - antibiotics |
| - pharmacodynamics |
| - resistance |
| - tabular |
| task_categories: |
| - tabular-classification |
| size_categories: |
| - n<1k |
| --- |
| |
| ABX-PD-009 Inoculum Effect Coherence |
|
|
| Purpose |
|
|
| Detect disproportionate efficacy loss at higher bacterial loads. |
|
|
| The key pattern |
|
|
| - inoculum rises |
| - exposure stays stable |
| - MIC stays stable |
| - killing drops too much |
|
|
| Files |
|
|
| - data/train.csv |
| - data/test.csv |
| - scorer.py |
|
|
| Schema |
|
|
| Each row is one inoculum condition in an ordered series. |
|
|
| Required columns |
|
|
| - row_id |
| - series_id |
| - inoculum_rank |
| - organism |
| - strain_id |
| - antibiotic_name |
| - antibiotic_class |
| - exposure_index |
| - mic_mg_L |
| - cfu0_log10 |
| - cfu24_log10 |
| - kill_24_log10 |
| - media |
| - assay_method |
| - source_type |
| - inoculum_effect_signal |
| - earliest_inoculum_effect |
| |
| Labels |
| |
| - inoculum_effect_signal |
| - 1 for rows at or after the first detected disproportionate loss |
| |
| - earliest_inoculum_effect |
| - 1 only for the first detected row in that series |
| |
| Evaluation |
| |
| Run |
| |
| - python scorer.py --path data/test.csv |
| |
| Scorer logic in v1 |
| |
| - baseline is inoculum_rank 1 |
| - event triggers when |
| - cfu0 rises by 1.0 log10 or more |
| - kill drops by 0.8 log10 or more vs baseline |
| - exposure_index stays within 10 percent of baseline |
| - MIC stays within 2 fold of baseline |
| |
