Derivation Web

source_e8706ad99154413c

by researka:v2 · 2026-07-05 05:59:21.062781+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": "5c993ba1-5ebb-4a12-b4dc-a4fe2418a927", "sources": [{"directness": "primary", "doi": "10.65205/jcct.2026.e3516", "risk_of_bias": "not appraised in public sidecar", "study": "A Retrieval-Augmented Generation Framework for Traditional Chinese Medicine Herb Recommendation Using Symptom-Focused and Ingredient-Based Embeddings"}, {"directness": "primary", "doi": "10.48550/arxiv.2602.07086", "risk_of_bias": "not appraised in public sidecar", "study": "Evaluating Retrieval-Augmented Generation Variants for Natural Language-Based SQL and API Call Generation"}, {"directness": "primary", "doi": "10.64898/2026.01.24.26344477", "risk_of_bias": "not appraised in public sidecar", "study": "A retrieval-augmented generation large language model framework for accurate dementia identification from electronic health records"}, {"directness": "primary", "doi": "10.1109/acdsa67686.2026.11467963", "risk_of_bias": "not appraised in public sidecar", "study": "Integrating Dense, Sparse, and Graph-Based Approaches in Financial Data Analysis for a Retrieval-Augmented Generation Framework"}, {"directness": "primary", "doi": "10.30871/jaic.v10i1.11738", "risk_of_bias": "not appraised in public sidecar", "study": "Improving Retrieval-Augmented Generation Performance Using the MAF-RAG Architecture, EVR–VOR Vector Retrieval, and Multi-Agent Fallback Reasoning"}]}

{
  "researka_object_type": "publication_sidecar",
  "researka_publication_id": "5c993ba1-5ebb-4a12-b4dc-a4fe2418a927",
  "researka_submission_id": "5e31a86d-9e6a-499c-80d8-e1e5c020abe3",
  "sidecar_name": "risk_of_bias.json",
  "sidecar_url": "https://api.researka.org/publications/5c993ba1-5ebb-4a12-b4dc-a4fe2418a927/sidecars/risk_of_bias.json"
}