First, Do No Harm (With LLMs): Mitigating Racial Bias via Agentic Workflows explores An agentic workflow that leverages retrieval to mitigate racial bias in LLM-generated medical cases and differential diagnoses, with code available.. Commercial viability score: 7/10 in Medical AI Bias Mitigation.
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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.
Freshness
Canonical route: /paper/first-do-no-harm-with-llms-mitigating-racial-bias-via-agentic-workflows
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Proof Quality
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Agent Handoff
Canonical ID first-do-no-harm-with-llms-mitigating-racial-bias-via-agentic-workflows | Route /paper/first-do-no-harm-with-llms-mitigating-racial-bias-via-agentic-workflows
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/first-do-no-harm-with-llms-mitigating-racial-bias-via-agentic-workflowsMCP example
{
"tool": "get_paper",
"arguments": {
"arxiv_id": "2604.18038"
}
}source_context
{
"surface": "paper",
"mode": "paper",
"query": "First, Do No Harm (With LLMs): Mitigating Racial Bias via Agentic Workflows",
"normalized_query": "2604.18038",
"route": "/paper/first-do-no-harm-with-llms-mitigating-racial-bias-via-agentic-workflows",
"paper_ref": "first-do-no-harm-with-llms-mitigating-racial-bias-via-agentic-workflows",
"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.
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Dimensions overall score 7.0
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