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/ordergrad-optimizing-beyond-the-mean-with-order-statistic-policy-gradient-estimation
Page-specific freshness sourced from this paper's evidence receipt and score bundle.
Agent Handoff
Canonical ID ordergrad-optimizing-beyond-the-mean-with-order-statistic-policy-gradient-estimation | Route /signal-canvas/ordergrad-optimizing-beyond-the-mean-with-order-statistic-policy-gradient-estimation
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/ordergrad-optimizing-beyond-the-mean-with-order-statistic-policy-gradient-estimationMCP example
{
"tool": "search_signal_canvas",
"arguments": {
"mode": "paper",
"paper_ref": "ordergrad-optimizing-beyond-the-mean-with-order-statistic-policy-gradient-estimation",
"query_text": "Summarize OrderGrad: Optimizing Beyond the Mean with Order-Statistic Policy Gradient Estimation"
}
}source_context
{
"surface": "signal_canvas",
"mode": "paper",
"query": "OrderGrad: Optimizing Beyond the Mean with Order-Statistic Policy Gradient Estimation",
"normalized_query": "2606.06096",
"route": "/signal-canvas/ordergrad-optimizing-beyond-the-mean-with-order-statistic-policy-gradient-estimation",
"paper_ref": "ordergrad-optimizing-beyond-the-mean-with-order-statistic-policy-gradient-estimation",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Claims: 1
References: Pending verification
Proof: Verification pending
Freshness state: computing
Source paper: OrderGrad: Optimizing Beyond the Mean with Order-Statistic Policy Gradient Estimation
PDF: https://arxiv.org/pdf/2606.06096v1
Repository: https://github.com/paavo5/ordergrad
Source count: 4
Coverage: 83%
Last proof check: 2026-06-06T11:26:35.831Z
Signal Canvas receipt window
/buildability/ordergrad-optimizing-beyond-the-mean-with-order-statistic-policy-gradient-estimation
Subject: OrderGrad: Optimizing Beyond the Mean with Order-Statistic Policy Gradient Estimation
Verdict
Ignore
Preparing verified analysis
Dimensions overall score 0.0
{"file name": "input.pdf", "number of pages": 42, "author": "Paavo Parmas; Yongmin Kim; Kohsei Matsutani; Shota Takashiro; Soichiro Nishimori; Takeshi Kojima; Yusuke Iwasawa; Yutaka Matsuo"
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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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.
Receipt path
/buildability/ordergrad-optimizing-beyond-the-mean-with-order-statistic-policy-gradient-estimation
Paper ref
ordergrad-optimizing-beyond-the-mean-with-order-statistic-policy-gradient-estimation
arXiv id
2606.06096
Generated at
2026-06-06T11:26:35.831Z
Evidence freshness
fresh
Last verification
2026-06-06T11:26:35.831Z
Sources
4
References
0
Coverage
83%
Lineage hash
8c13f3d5556556b09560b0ccf6d253c5c9db3dfbbcabf1e4fa258fc6a26c8c26
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