This equation captures one of the core mathematical components of the system. N ∑i ∑j cij) reports the mean number of flagged criteria across all evaluated scenarios. A model may
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Emergent Strategic Reasoning Risks in AI: A Taxonomy-Driven Evaluation Framework explores ESRRSim is a taxonomy-driven framework for evaluating emergent strategic reasoning risks like deception and evaluation gaming in LLMs.. Commercial viability score: 7/10 in AI Safety & Reasoning.
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Page Freshness
Canonical route: /paper/emergent-strategic-reasoning-risks-in-ai-a-taxonomy-driven-evaluation-framework
Page-specific freshness sourced from this paper's evidence receipt and score bundle.
Agent Handoff
Canonical ID emergent-strategic-reasoning-risks-in-ai-a-taxonomy-driven-evaluation-framework | Route /paper/emergent-strategic-reasoning-risks-in-ai-a-taxonomy-driven-evaluation-framework
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/emergent-strategic-reasoning-risks-in-ai-a-taxonomy-driven-evaluation-frameworkMCP example
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}Paper proof page receipt window
/buildability/emergent-strategic-reasoning-risks-in-ai-a-taxonomy-driven-evaluation-framework
Subject: Emergent Strategic Reasoning Risks in AI: A Taxonomy-Driven Evaluation Framework
Verdict
Watch
Verdict is Watch because viability or proof quality is intermediate and should be re-evaluated before execution.
Time to first demo
Insufficient data
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Structured compute envelope
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No data, compute, hardware, memory, latency, dependency, or serving requirement receipt is attached.
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Dimensions overall score 7.0
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Visual citation anchors from the paper document graph.
This equation captures one of the core mathematical components of the system. N ∑i ∑j cij) reports the mean number of flagged criteria across all evaluated scenarios. A model may
Page and bbox are available; crop image is pending.
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References are not available from the internal index yet.
Receipt path
/buildability/emergent-strategic-reasoning-risks-in-ai-a-taxonomy-driven-evaluation-framework
Paper ref
emergent-strategic-reasoning-risks-in-ai-a-taxonomy-driven-evaluation-framework
arXiv id
2604.22119
Generated at
2026-04-27T20:16:05.063Z
Evidence freshness
fresh
Last verification
2026-04-27T20:16:05.063Z
Sources
3
References
0
Coverage
50%
Lineage hash
03281f78b02ca13b940b2a8918da6ed5d384e85797f7e04acc8d9602edcc9ec6
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
This equation captures one of the core mathematical components of the system. DR(τ) = N where 1[·] is the indicator function. We set τ = 0.3 as the default
Page and bbox are available; crop image is pending.
This equation captures one of the core mathematical components of the system. si = ∑M j=1 cij · wj ∑M j=1 wj where cij ∈{0, 1} is the binary judgment fo
Page and bbox are available; crop image is pending.
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