proof blockPage 568%
This equation captures one of the core mathematical components of the system. paper has ≥3 substantive reviews, an unambiguous AC decision with articulated reasoning, and ≥
What Makes a Good AI Review? Concern-Level Diagnostics for AI Peer Review explores This paper introduces a diagnostic framework for evaluating AI-generated reviews at the concern level, moving beyond simple verdict agreement to assess how AI systems identify and prioritize review concerns.. Commercial viability score: 3/10 in AI Evaluation.
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Page Freshness
Canonical route: /paper/what-makes-a-good-ai-review-concern-level-diagnostics-for-ai-peer-review
Page-specific freshness sourced from this paper's evidence receipt and score bundle.
Agent Handoff
Canonical ID what-makes-a-good-ai-review-concern-level-diagnostics-for-ai-peer-review | Route /paper/what-makes-a-good-ai-review-concern-level-diagnostics-for-ai-peer-review
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/what-makes-a-good-ai-review-concern-level-diagnostics-for-ai-peer-reviewMCP example
{
"tool": "get_paper",
"arguments": {
"arxiv_id": "2604.19998"
}
}source_context
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"query": "What Makes a Good AI Review? Concern-Level Diagnostics for AI Peer Review",
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}Paper proof page receipt window
/buildability/what-makes-a-good-ai-review-concern-level-diagnostics-for-ai-peer-review
Subject: What Makes a Good AI Review? Concern-Level Diagnostics for AI Peer Review
Verdict
Ignore
Verdict is Ignore because current viability and proof state do not clear the buildability gate.
Time to first demo
Insufficient data
No first-demo timestamp, owner estimate, or elapsed demo receipt is attached to this surface.
Structured compute envelope
Insufficient data
No data, compute, hardware, memory, latency, dependency, or serving requirement receipt is attached.
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Dimensions overall score 3.0
Visual citation anchors from the paper document graph.
This equation captures one of the core mathematical components of the system. paper has ≥3 substantive reviews, an unambiguous AC decision with articulated reasoning, and ≥
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Receipt path
/buildability/what-makes-a-good-ai-review-concern-level-diagnostics-for-ai-peer-review
Paper ref
what-makes-a-good-ai-review-concern-level-diagnostics-for-ai-peer-review
arXiv id
2604.19998
Generated at
2026-04-23T05:10:45.856Z
Evidence freshness
fresh
Last verification
2026-04-23T05:10:45.856Z
Sources
3
References
0
Coverage
50%
Lineage hash
fe649d693171b772f4ba57028ac6b97bc2d72758dedf003a6c0b77f475c8c5eb
Canonical opportunity-kernel lineage hash.
External signature
unsigned_external
No founder, registry, pilot, or production-adoption signature is attached to this receipt.
Verification
not_verified
Verification is blocked until an external signature is provided.
Pending verification refs / 3 sources / Verification pending
repo_url
references
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This equation captures one of the core mathematical components of the system. rcl = decisive-blocker recall on rejected papers; FDR = false decisive rate on accepted papers; Res.
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This equation captures one of the core mathematical components of the system. esc = resolved-escalation on accepted papers; DecP = decisive precision (strict) on rejected papers
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