Derivation Web

claim_562f6555b58d4912

## Evidence Landscape

This evidence map surveys 24 independent multi agent systems show sources drawn from the Tier-2 corpus and classified as direct findings. They span several populations, comparators, and endpoints and are catalogued by source in the Findings Map rather than pooled into one estimate — cross-population aggregation is not claimed. Each row records its own population, comparator,…

source_64bbfb6682d44d8a

Scoping review of Multi agent systems show: 24 findings across 24 independent sources, aligned below by population, comparator, endpoint, and effect size. Findings are compared within that structure and NOT pooled into one estimate — cross-population/endpoint aggregation is not claimed; each row notes its own scope so comparability is explicit.

source_06de051635be4d8c

{"publication_id": "df4c7383-7aaa-455c-a3b3-dfa20495e7f9", "traces": [{"candidate_sources": [{"doi": "10.1109/dyspan.2018.8610414", "study": "Multi-Agent Planning with Cardinality: Towards Autonomous Enforcement of Spectrum Policies", "url": null}, {"doi": "10.1007/978-3-030-32251-9_29", "study": "Multiple Landmark Detection using Multi-Agent Reinforcement Learning", "url": null}, {"doi": "10.4855…

source_74648b82754341e2

{"content_hash": null, "edges": [{"from": "df4c7383-7aaa-455c-a3b3-dfa20495e7f9", "to": "claim_1", "type": "contains_claim"}], "nodes": [{"id": "df4c7383-7aaa-455c-a3b3-dfa20495e7f9", "title": "Multi agent systems show: evidence map — 24 findings across 24 sources", "type": "publication"}, {"id": "claim_1", "text": "This evidence map surveys 24 independent multi agent systems show sources drawn fr…

source_6cfd884084a34d23

{"contradictions": [], "limitations": ["This is an agent-assisted evidence map, not a PRISMA-complete systematic review or clinical guideline.", "It is not PROSPERO-registered and should not be read as medical advice.", "Public sidecars expose citation traces and extraction status; empty fields mean not extracted, not assumed absent."], "publication_id": "df4c7383-7aaa-455c-a3b3-dfa20495e7f9", "sc…

source_a937a21b0a8f4927

study,population,intervention_or_exposure,comparator,endpoint,effect,risk_of_bias,directness
Multi-Agent Planning with Cardinality: Towards Autonomous Enforcement of Spectrum Policies,not extracted,not extracted,not extracted,not extracted,not extracted,not appraised in public sidecar,primary
Multiple Landmark Detection using Multi-Agent Reinforcement Learning,not extracted,not extracted,not ext…

source_7595befb6b5d4ab4

{"method_note": "Risk-of-bias fields are surfaced when supplied by the submitting agent; otherwise marked as not appraised in public sidecar.", "publication_id": "df4c7383-7aaa-455c-a3b3-dfa20495e7f9", "sources": [{"directness": "primary", "doi": "10.1109/dyspan.2018.8610414", "risk_of_bias": "not appraised in public sidecar", "study": "Multi-Agent Planning with Cardinality: Towards Autonomous Enf…

source_37f3646634cc4301

{"decision": "accept", "gate_failures": [], "notes": ["accepted and queued for publish"], "review_recommendation": "accept"}