Data quality updated

README.md

@@ -173,6 +173,15 @@ Despite its diversity, the dataset has inherent limitations. The SIIB system is
 
 In synthetic engineering datasets, extrinsic bias operates differently than in datasets derived from human-generated text or behavioral data. That said, several structural biases warrant explicit acknowledgment. The dataset is built around power system conventions, standards, and test cases that predominantly originate from North American and European grid infrastructure traditions, specifically 60 Hz nominal frequency and grid parameters typical of North American distribution systems. Grids in the Global South, particularly in Sub-Saharan Africa, South Asia, and rural and remote communities in the Arctic and northern regions, often operate under fundamentally different conditions: weaker grids with lower short-circuit ratios, 50 Hz nominal frequency, different fault standards, and less standardized inverter hardware. The SIIB system, as parameterized here, may not fully reflect those conditions. 
 
+## 4.3- Authenticity and Reliability
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+Every file in the dataset is a direct output of simulation models built and executed by the dataset creators, using the wrangling pipeline described previously. The identity of the dataset's creators and their institutional affiliations are unambiguous and verifiable through the associated publication and Hugging Face repository metadata; these are currently anonymized to support a double-blind review policy. The dataset is registered with a globally unique and persistent Digital Object Identifier (DOI). Users should cite this DOI rather than the Hugging Face URL, as DOIs provide permanent, resolver-independent access independent of repository infrastructure changes.
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+The nature of the signals provided by each CSV file is discussed previously. All wrangling operations are purely structural and do not modify signal values. The integrity of the exported files was verified by randomly cross-checking the CSV files associated with 100 scenarios against the corresponding Scope outputs in MATLAB Simulink and PSCAD prior to packaging, confirming full agreement between stored values and simulation ground truth. In summary, as a synthetic dataset, both authenticity and reliability are established through controlled simulation pipelines, the use of well-defined physical models, and complete traceability from scenario definition to output signals. Users can verify the provenance of any scenario by cross-referencing the xxxx_meta.csv file with the simulation model documentation provided in this dataset card. Note that no cryptographic integrity checks, e.g., hashes, are currently provided to verify file-level integrity after distribution.
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+Users can independently verify the dataset's reliability through several mechanisms. The physical relationship between d-q signals provides a built-in consistency check. Active power P should equal V_d × i_d + V_q × i_q, and reactive power Q should equal V_q × i_d – V_d × i_q at every time step. Deviations beyond floating-point precision would indicate a data integrity issue. Under steady-state conditions (Trig = False), V_q should converge toward zero and P and Q should stabilize at values consistent with P_ref and Q_ref recorded in xxxx_meta.csv. Users can verify this for any scenario by inspecting the terminal portion of the trajectory after the trigger transitions to False. 
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