Evidence Receipt. Related Resources.
Evidence Receipt. Related Resources.
Compared to this week’s papers
Verification pending
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Route this paper proof surface into REST, MCP, or developer workflows while preserving the same evidence receipt and related-resource context.
Page Freshness
Canonical route: /signal-canvas/addressing-image-authenticity-when-cameras-use-generative-ai
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 addressing-image-authenticity-when-cameras-use-generative-ai | Route /signal-canvas/addressing-image-authenticity-when-cameras-use-generative-ai
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/addressing-image-authenticity-when-cameras-use-generative-aiMCP example
{
"tool": "search_signal_canvas",
"arguments": {
"mode": "paper",
"paper_ref": "addressing-image-authenticity-when-cameras-use-generative-ai",
"query_text": "Summarize Addressing Image Authenticity When Cameras Use Generative AI"
}
}source_context
{
"surface": "signal_canvas",
"mode": "paper",
"query": "Addressing Image Authenticity When Cameras Use Generative AI",
"normalized_query": "2604.21879",
"route": "/signal-canvas/addressing-image-authenticity-when-cameras-use-generative-ai",
"paper_ref": "addressing-image-authenticity-when-cameras-use-generative-ai",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Claims: 1
References: Pending verification
Proof: Verification pending
Freshness state: computing
Source paper: Addressing Image Authenticity When Cameras Use Generative AI
PDF: https://arxiv.org/pdf/2604.21879v1
Repository: https://github.com/cvpr-org/author-kit
Source count: 4
Coverage: 50%
Last proof check: 2026-04-24T20:29:38.720Z
Signal Canvas receipt window
/buildability/addressing-image-authenticity-when-cameras-use-generative-ai
Subject: Addressing Image Authenticity When Cameras Use Generative AI
Verdict
Watch
Verdict is Watch because viability or proof quality is intermediate and should be re-evaluated before execution.
Preparing verified analysis
Dimensions overall score 6.0
{"file name": "input.pdf", "number of pages": 13, "author": "Umar Masud; Abhijith Punnappurath; Luxi Zhao; David B. Lindell; Michael S. Brown", "title": "Addressing Image Authenticity When Cameras Use Generative AI"
Implication not extracted yet.
partial
Related resources will appear here when this paper maps cleanly to topic, benchmark, or dataset surfaces.
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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.
Receipt path
/buildability/addressing-image-authenticity-when-cameras-use-generative-ai
Paper ref
addressing-image-authenticity-when-cameras-use-generative-ai
arXiv id
2604.21879
Generated at
2026-04-24T20:29:38.720Z
Evidence freshness
stale
Last verification
2026-04-24T20:29:38.720Z
Sources
4
References
0
Coverage
50%
Lineage hash
3491982a1ee3e543b2ea6cbc14628e986eeb74896185df21f5a18104e4a4eb28
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 / 4 sources / Verification pending
references
proof_status