bioRxiv / medRxiv
open access
CC BY-NC-ND 4.0
Characterizing large language model generative artificial intelligence variability in the production of objective structured clinical examination stations
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Right Answer, Wrong Reason: Accuracy, Consistency, and Consensus Are Misleading Indicators of LLM Faithfulness in Clinical Decision Support#1117148
- Improving Medical Calculation of LLMs with Embedded Coding#1115864
- Clinical Validation of a Generative AI System for Diagnosing Ampullary Lesions: A Multicenter Study.#308771
- Uncertainty-Aware Calibrated Clinical Text Classification with Large Language Models#1070710
- Using Generative AI to Appraise the Quality of Medical Education Research Studies: Agreement Between AI-Generated and Human MERSQI Scores.#247562
Record · ID 651099
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive