Compared to this week’s papers
Evidence fresh
Claims: 0
References: 0
Proof: unverified
Freshness: fresh
Source paper: Intelligent Pathological Diagnosis of Gestational Trophoblastic Diseases via Visual-Language Deep Learning Model
PDF: https://arxiv.org/pdf/2603.02704v1
Source count: 0
Coverage: 17%
Canonical paper trust state plus paper-specific synthesis and commercialization judgment.
Paper mode stays anchored to the canonical paper kernel before it broadens into citations and next actions.
Paper mode stays anchored to the canonical paper kernel before it broadens into citations and next actions.
Shared `source_context` now powers Build Loop, Talent, workspace saves, and browser deep links.
Citation-first answers with explicit evidence receipts, disagreement handling, commercialization framing, and next actions.
Canonical paper receipt
distribution readiness has not been computed yet
repo_url
Freshness: fresh
Proof: unverified
Repo: missing
Coverage: 17%
References: 0
Sources: 0
Lineage: not recorded
Last verification: Unknown
Canonical Paper Receipt
distribution readiness has not been computed yet
repo_url
Freshness: fresh
Proof: unverified
Repo: missing
Coverage: 17%
References: 0
Sources: 0
Lineage: not recorded
Last verification: Unknown
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Dimensions overall score 7.0
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Yuhang Liu
Tsinghua University, Beijing, China
Yueyang Cang
Tsinghua University, Beijing, China
Wenge Que
Donghua University, Shanghai, China
Xinru Bai
Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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