Evidence Receipt. Related Resources.
Evidence Receipt. Related Resources.
Compared to this week’s papers
Verification pending
Use This Via API or MCP
Signal Canvas is the citation-first public layer for turning one paper into a structured commercialization narrative. Use it to hand off into REST, MCP, Build Loop, and launch-pack execution without losing source lineage.
Use This Via API or MCP
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/idscd-identifying-training-datasets-through-semantic-correlation-descriptors
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 idscd-identifying-training-datasets-through-semantic-correlation-descriptors | Route /signal-canvas/idscd-identifying-training-datasets-through-semantic-correlation-descriptors
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/idscd-identifying-training-datasets-through-semantic-correlation-descriptorsMCP example
{
"tool": "search_signal_canvas",
"arguments": {
"mode": "paper",
"paper_ref": "idscd-identifying-training-datasets-through-semantic-correlation-descriptors",
"query_text": "Summarize idSCD: Identifying Training Datasets through Semantic Correlation Descriptors"
}
}source_context
{
"surface": "signal_canvas",
"mode": "paper",
"query": "idSCD: Identifying Training Datasets through Semantic Correlation Descriptors",
"normalized_query": "2605.30462",
"route": "/signal-canvas/idscd-identifying-training-datasets-through-semantic-correlation-descriptors",
"paper_ref": "idscd-identifying-training-datasets-through-semantic-correlation-descriptors",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Claims: 1
References: Pending verification
Proof: Verification pending
Freshness state: computing
Source paper: idSCD: Identifying Training Datasets through Semantic Correlation Descriptors
PDF: https://arxiv.org/pdf/2605.30462v1
Source count: 3
Coverage: 50%
Last proof check: 2026-06-01T20:25:19.441Z
Signal Canvas receipt window
/buildability/idscd-identifying-training-datasets-through-semantic-correlation-descriptors
Subject: idSCD: Identifying Training Datasets through Semantic Correlation Descriptors
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 7.0
No public code linked for this paper yet.
{"file name": "input.pdf", "number of pages": 16, "author": "Andrada Gobeaja; Ionut Hodoroaga; Elena Burceanu; Marius Leordeanu", "title": "idSCD: Identifying Training Datasets through Semantic Correlation Descriptors"
Implication not extracted yet.
partial
Related resources will appear here when this paper maps cleanly to topic, benchmark, or dataset surfaces.
Use an AI coding agent to implement this research.
Lightweight coding agent in your terminal.
Agentic coding tool for terminal workflows.
AI agent mindset installer and workflow scaffolder.
AI-first code editor built on VS Code.
Free, open-source editor by Microsoft.
Estimated $9K - $13K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
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/idscd-identifying-training-datasets-through-semantic-correlation-descriptors
Paper ref
idscd-identifying-training-datasets-through-semantic-correlation-descriptors
arXiv id
2605.30462
Generated at
2026-06-01T20:25:19.441Z
Evidence freshness
stale
Last verification
2026-06-01T20:25:19.441Z
Sources
3
References
0
Coverage
50%
Lineage hash
fae930f19734487a75741df9038e8ba0fade8b100557ed0334158793fa1dc52f
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