This analysis reveals which molecular properties best predict whether chemicals break down naturally in the environment. We identified the strongest predictors, spotted outliers that could skew models, and found three binary features that dramatically boost biodegradability odds to 92–95%. Whether you're building QSAR models or just curious about green chemistry, these findings show which features matter most.
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