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Grounded Adjudication of Variations across Extracted TimeLines (GAVEL): Comparing Clinical Timelines Against Their Case Reports

arXiv 2609.13475 ↗First posted 11 Sep 2026cs.AIcited by 0

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Abstract (arXiv)

Existing pipelines for clinical timeline extraction from case reports are evaluated using an expert reference and are limited by imperfect reference annotations and imprecise event alignment. We developed GAVEL, an LLM judge protocol that compares two timelines with the case report and returns a discrepancy type, verdict, and report passage for each difference. We evaluated the event matcher, reviewed 2,738 findings from GPT5.6sol and DeepSeek V3.2, ranked six LLM extractors and two human annotators, and tested GAVEL guided merging. True match rates were 60% immediately below and 48% immediately above the 0.10 cutoff. Manual review confirmed 89.4% and 88.6% of findings. Across 126 reports, merged timelines were preferred in 77.0% of comparisons (95% CI, 69.8 to 84.1%) and reduced discrepancies attributed to the evaluated timeline from 7.63 to 0.85 per report. GAVEL supports report-based comparison and revision without treating either timeline as ground truth.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 10 of its 13 references that are in the map. First posted on arXiv 11 Sep 2026.

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References · 10

  1. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,626
  2. 2023G-Eval: NLG Evaluation using GPT-4 with Better Human Alignmentcited by 2,276
  3. 2023FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generationcited by 1,282
  4. 2024Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preferencecited by 1,184
  5. 2020Domain-Specific Language Model Pretraining for Biomedical Natural Language Processingcited by 1,009
  6. 2024LLM Evaluators Recognize and Favor Their Own Generationscited by 686
  7. 2025TIMER: Temporal Instruction Modeling and Evaluation for Longitudinal Clinical Recordscited by 34
  8. 2025A Large-Language Model Framework for Relative Timeline Extraction from PubMed Case Reportscited by 10
  9. 2025PMOA-TTS: Introducing the PubMed Open Access Textual Times Series Corpuscited by 3
  10. 2026Temporally Phenotyping GLP-1RA Case Reports with Large Language Models: A Textual Time Series Corpus and Risk Modelingcited by 2

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