{"publication_id":"937decba-8b7a-4b7d-a0bb-38a0fc3e75e5","content_hash":"sha256:4f0263b93f1f3af869cd9eb7463d6f5ede6fdb1b20c8fadeaf80ecf42628546f","nodes":[{"id":"937decba-8b7a-4b7d-a0bb-38a0fc3e75e5","type":"publication","title":"RAG-based methods improve accuracy on medical question answering benchmarks (MedQA, MedMCQA, MRCOG) across various base models without task-specific fine-tuning"},{"id":"claim_1","type":"claim","text":"Across 5 independently cited sources, the evidence converges on one bounded claim: rAG-based methods improve accuracy on medical question answering benchmarks (MedQA, MedMCQA, MRCOG) across various base models without task-specific fine-tuning. Effect sizes vary by subgroup and are listed per source below rather than pooled into a single estimate."},{"id":"claim_2","type":"claim","text":"Interpretation note:** This is a hypothesis-generating alpha memo, not confirmatory evidence; subgroup or context-derived claims require independent replication."},{"id":"claim_3","type":"claim","text":"The surprise is the bounded heterogeneity: the cited direct receipts do not support one uniform effect estimate, so the useful alpha is the specific receipt map and its unresolved spread."},{"id":"claim_4","type":"claim","text":"Treat this as a receipt map for choosing the next extraction, not as evidence that the topic has one unified effect. The only publishable claim is the separation of streams until a repeated direct-source cluster supports one endpoint-specific thesis."},{"id":"claim_5","type":"claim","text":"_No direct opposing receipt was selected by this run. Treat that as a bundle limitation, not a claim that the wider literature has no counter-evidence._"},{"id":"source_1","type":"source","study":"Quality Outweighs Quantity: Advancing Medical Question Answering with RAG-MCP Muti-Agent LLM Framework and Curated Knowledge Databases","year":2026,"doi":"10.1109/ccwc67433.2026.11393764","url":null,"population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary"},{"id":"source_2","type":"source","study":"Bridging Rationales and Relations: The Graph-Rationale-Guided Retrieval-Augmented Generation in Medical QA","year":2026,"doi":"10.54097/vee3xx26","url":null,"population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary"},{"id":"source_3","type":"source","study":"Improving Retrieval-Augmented Generation in Medicine with Iterative Follow-up Questions.","year":2025,"doi":"10.1142/9789819807024_0015","url":"https://pubmed.ncbi.nlm.nih.gov/39670371/","population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary"},{"id":"source_4","type":"source","study":"Reasoning Over Pre-training: Evaluating LLM Performance and Augmentation in Women's Health","year":2025,"doi":"10.1101/2025.05.22.25328162","url":null,"population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary"},{"id":"source_5","type":"source","study":"A Novel RAG Framework with Knowledge-Enhancement for Biomedical Question Answering","year":2024,"doi":"10.1109/bibm62325.2024.10822837","url":null,"population":"not extracted","intervention_or_exposure":"not extracted","comparator":"not extracted","endpoint":"not extracted","effect":"not extracted","risk_of_bias":"not appraised in public sidecar","directness":"primary"}],"edges":[{"from":"937decba-8b7a-4b7d-a0bb-38a0fc3e75e5","to":"claim_1","type":"contains_claim"},{"from":"937decba-8b7a-4b7d-a0bb-38a0fc3e75e5","to":"claim_2","type":"contains_claim"},{"from":"937decba-8b7a-4b7d-a0bb-38a0fc3e75e5","to":"claim_3","type":"contains_claim"},{"from":"937decba-8b7a-4b7d-a0bb-38a0fc3e75e5","to":"claim_4","type":"contains_claim"},{"from":"937decba-8b7a-4b7d-a0bb-38a0fc3e75e5","to":"claim_5","type":"contains_claim"}],"screening":{"identified":5,"screened":5,"excluded":0,"included":5,"included_or_retained":5,"flow":["identified","screened","excluded_with_reasons","included"],"wording":"5 candidate receipts retained after source retrieval, deduplication, and topic filtering. This is an evidence-map screening trace, not a PRISMA full-text exclusion audit.","exclusion_reasons":["No PRISMA full-text exclusion-stage filter was applied."]}}