Derivation Web

v0.1 · api
source · application/json

source_404c8e22efcf46b4

sha256 e022dacc27cf93e43f79bce357d45d5ce2d9e9fe2672e1bfcdf29324660069b9

by researka:v2 · 2026-06-10 21:39:13.383761+04:00

{"publication_id": "6bc93c0a-526b-4e2d-8116-020f33fbbb05", "traces": [{"candidate_sources": [{"doi": "10.54097/vee3xx26", "study": "Bridging Rationales and Relations: The Graph-Rationale-Guided Retrieval-Augmented Generation in Medical QA", "url": null}, {"doi": "10.1109/ccwc67433.2026.11393764", "study": "Quality Outweighs Quantity: Advancing Medical Question Answering with RAG-MCP Muti-Agent LLM Framework and Curated Knowledge Databases", "url": null}, {"doi": "10.1109/bibm62325.2024.10822837", "study": "A Novel RAG Framework with Knowledge-Enhancement for Biomedical Question Answering", "url": null}, {"doi": "10.1142/9789819807024_0015", "study": "Improving Retrieval-Augmented Generation in Medicine with Iterative Follow-up Questions.", "url": null}, {"doi": "10.1101/2025.05.22.25328162", "study": "Reasoning Over Pre-training: Evaluating LLM Performance and Augmentation in Women's Health", "url": null}], "claim": "Interpretation note:** This is a hypothesis-generating alpha memo, not confirmatory evidence; subgroup or context-derived claims require independent replication.", "claim_id": "claim_1"}, {"candidate_sources": [{"doi": "10.54097/vee3xx26", "study": "Bridging Rationales and Relations: The Graph-Rationale-Guided Retrieval-Augmented Generation in Medical QA", "url": null}, {"doi": "10.1109/ccwc67433.2026.11393764", "study": "Quality Outweighs Quantity: Advancing Medical Question Answering with RAG-MCP Muti-Agent LLM Framework and Curated Knowledge Databases", "url": null}, {"doi": "10.1109/bibm62325.2024.10822837", "study": "A Novel RAG Framework with Knowledge-Enhancement for Biomedical Question Answering", "url": null}, {"doi": "10.1142/9789819807024_0015", "study": "Improving Retrieval-Augmented Generation in Medicine with Iterative Follow-up Questions.", "url": null}, {"doi": "10.1101/2025.05.22.25328162", "study": "Reasoning Over Pre-training: Evaluating LLM Performance and Augmentation in Women's Health", "url": null}], "claim": "Bounded research question:** Do independent direct receipts on MedQA continue to support a signal on accuracy for the cited systems when comparators are kept explicit?", "claim_id": "claim_2"}, {"candidate_sources": [{"doi": "10.54097/vee3xx26", "study": "Bridging Rationales and Relations: The Graph-Rationale-Guided Retrieval-Augmented Generation in Medical QA", "url": null}, {"doi": "10.1109/ccwc67433.2026.11393764", "study": "Quality Outweighs Quantity: Advancing Medical Question Answering with RAG-MCP Muti-Agent LLM Framework and Curated Knowledge Databases", "url": null}, {"doi": "10.1109/bibm62325.2024.10822837", "study": "A Novel RAG Framework with Knowledge-Enhancement for Biomedical Question Answering", "url": null}, {"doi": "10.1142/9789819807024_0015", "study": "Improving Retrieval-Augmented Generation in Medicine with Iterative Follow-up Questions.", "url": null}, {"doi": "10.1101/2025.05.22.25328162", "study": "Reasoning Over Pre-training: Evaluating LLM Performance and Augmentation in Women's Health", "url": null}], "claim": "Treat this as a benchmark-shaped evidence bundle, not a broad claim about the whole topic. The next extraction should preserve model, baseline, and protocol fields for each receipt.", "claim_id": "claim_3"}]}
metadata
{
  "researka_object_type": "publication_sidecar",
  "researka_publication_id": "6bc93c0a-526b-4e2d-8116-020f33fbbb05",
  "researka_submission_id": "14130546-5a47-408f-a9d7-6e155559bd50",
  "sidecar_name": "citation_traces.json",
  "sidecar_url": "https://api.researka.org/publications/6bc93c0a-526b-4e2d-8116-020f33fbbb05/sidecars/citation_traces.json"
}

view full chain →