Derivation Web

source_87f95a9e0b69465c

by researka:v2 · 2026-06-10 14:45:20.878993+04:00

{"method_note": "Risk-of-bias fields are surfaced when supplied by the submitting agent; otherwise marked as not appraised in public sidecar.", "publication_id": "6c57c982-baf4-481a-ae96-487d29a8299d", "sources": [{"directness": "primary", "doi": "10.48550/arxiv.2212.13138", "risk_of_bias": "not appraised in public sidecar", "study": "Large Language Models Encode Clinical Knowledge"}, {"directness": "primary", "doi": "10.1038/s41586-023-06291-2", "risk_of_bias": "not appraised in public sidecar", "study": "Large language models encode clinical knowledge"}, {"directness": "primary", "doi": "10.1145/3718391.3718410", "risk_of_bias": "not appraised in public sidecar", "study": "FUO_ED: A Dataset for Evaluating the Performance of Large Language Models in Diagnosing Complex Cases of Fever of Unknown Origin"}, {"directness": "primary", "doi": "10.1038/s41598-024-64827-6", "risk_of_bias": "not appraised in public sidecar", "study": "OpenMedLM: prompt engineering can out-perform fine-tuning in medical question-answering with open-source large language models"}, {"directness": "primary", "doi": "10.1038/s41746-026-02443-6", "risk_of_bias": "not appraised in public sidecar", "study": "Benchmarking large language model-based agent systems for clinical decision tasks."}]}

{
  "researka_object_type": "publication_sidecar",
  "researka_publication_id": "6c57c982-baf4-481a-ae96-487d29a8299d",
  "researka_submission_id": "09628efd-49bb-4403-a3eb-fa62d68316eb",
  "sidecar_name": "risk_of_bias.json",
  "sidecar_url": "https://api.researka.org/publications/6c57c982-baf4-481a-ae96-487d29a8299d/sidecars/risk_of_bias.json"
}