Introduces power-law, logistic, and discrepancy-based tapers for correlation-based localization that suppress spurious correlations and often preserve more posterior ensemble variance than distance-based methods in synthetic reservoir assimilation tests.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
ML-specific code smells occur 41-94 times less often than general Python smells in 279 projects, with associations to commit frequency and domain but none for general smells or most other project characteristics.
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Comparing ML-Specific and General Python Code Smells Across Project Characteristics
ML-specific code smells occur 41-94 times less often than general Python smells in 279 projects, with associations to commit frequency and domain but none for general smells or most other project characteristics.