XrayClaw: Cooperative-Competitive Multi-Agent Alignment for Trustworthy Chest X-ray Diagnosis explores A multi-agent AI system that improves the trustworthiness and accuracy of chest X-ray diagnoses by simulating a cooperative-competitive clinical workflow.. Commercial viability score: 7/10 in Medical AI.
Use This Via API or MCP
This route is the stable paper-level surface for citations, viability, references, and downstream handoffs. Use it as the proof layer behind Signal Canvas, workspace creation, and launch-pack generation.
Page Freshness
Canonical route: /paper/xrayclaw-cooperative-competitive-multi-agent-alignment-for-trustworthy-chest-x-ray-diagnosis
This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.
Agent Handoff
Canonical ID xrayclaw-cooperative-competitive-multi-agent-alignment-for-trustworthy-chest-x-ray-diagnosis | Route /paper/xrayclaw-cooperative-competitive-multi-agent-alignment-for-trustworthy-chest-x-ray-diagnosis
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/xrayclaw-cooperative-competitive-multi-agent-alignment-for-trustworthy-chest-x-ray-diagnosisMCP example
{
"tool": "get_paper",
"arguments": {
"arxiv_id": "2604.02695"
}
}source_context
{
"surface": "paper",
"mode": "paper",
"query": "XrayClaw: Cooperative-Competitive Multi-Agent Alignment for Trustworthy Chest X-ray Diagnosis",
"normalized_query": "2604.02695",
"route": "/paper/xrayclaw-cooperative-competitive-multi-agent-alignment-for-trustworthy-chest-x-ray-diagnosis",
"paper_ref": "xrayclaw-cooperative-competitive-multi-agent-alignment-for-trustworthy-chest-x-ray-diagnosis",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Constellation, claims, and market context stay visible on the paper proof page even when commercialization rails are held back for incomplete proof receipts.
Research neighborhood
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Preparing verified analysis
Dimensions overall score 7.0
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