⚡ Bolt: [performance improvement] Replace iterrows with to_dict('records')

[alinelena]

💡 What: Replaced df.iterrows() with df.to_dict('records') in verify_processed_omol25.py, and updated downstream dictionary constructors and method calls (pq_row.to_dict() -> dict(pq_row)).
🎯 Why: df.iterrows() is a known pandas anti-pattern that creates significant performance overhead by yielding a new Series object for every single row. Furthermore, the original code ran it twice, storing pandas Series objects in memory which consumes a massive amount of memory for large dataframes.
📊 Impact: Expected to provide a massive speedup in iteration time (as dictionary conversions happen at the C-level) and drastically reduce memory overhead (native Python dictionaries are much lighter than pandas Series objects).
🔬 Measurement: Verify by running the data verification script on a large parquet dataset and observing the processing time drop.

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PR created automatically by Jules for task 8365578486972164348 started by @alinelena

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