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Analysis

This paper introduces ACT, a novel algorithm for detecting biblical quotations in Rabbinic literature, specifically addressing the limitations of existing systems in handling complex citation patterns. The high F1 score (0.91) and superior recall and precision compared to baselines demonstrate the effectiveness of ACT. The ability to classify stylistic patterns also opens avenues for genre classification and intertextual analysis, contributing to digital humanities.
Reference

ACT achieves an F1 score of 0.91, with superior Recall (0.89) and Precision (0.94).

Research#Geology🔬 ResearchAnalyzed: Jan 10, 2026 11:04

Machine Learning Boosts Lithological Interpretation in Deep-Sea Drilling

Published:Dec 15, 2025 16:59
1 min read
ArXiv

Analysis

This ArXiv article highlights the application of machine learning to improve the accuracy of lithological interpretation from well logs. The use of AI in this context can potentially revolutionize geological analysis in deep-sea drilling projects like IODP.
Reference

The article focuses on IODP expedition 390/393.