⚡ Bolt: [Optimize Pandas DataFrame Iteration in verify script]

[alinelena]

💡 What: Replaced df.iterrows() with df.to_dict('records') in verify_processed_omol25.py. Removed redundant .to_dict() methods on row items since they are native python dictionaries rather than pandas Series.
🎯 Why: Iterating over large pandas DataFrames via df.iterrows() is an established anti-pattern known to be extremely slow due to the overhead of creating Series objects for every single row.
📊 Impact: Massively reduces runtime overhead for the verification script, especially when validating large datasets where iteration becomes the bottleneck.
🔬 Measurement: Verify by running the verification scripts over a large .parquet dataset and observing a stark reduction in iteration time compared to the unpatched script. Also verified via existing automated tests in tests/test_verify_processed_omol25.py that core matching logics are unbroken.

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PR created automatically by Jules for task 15992796889034871065 started by @alinelena

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