This equation captures one of the core mathematical components of the system. invalid-profile models do not (d = 2.17, p = .001). Fourth, chain-of-thought training produces two
Before You Interpret the Profile: Validity Scaling for LLM Metacognitive Self-Report explores A framework for assessing LLM response validity, identifying construct-level invalid models and improving interpretability with code available.. Commercial viability score: 7/10 in LLM Evaluation.
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Canonical route: /paper/before-you-interpret-the-profile-validity-scaling-for-llm-metacognitive-self-report
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Canonical ID before-you-interpret-the-profile-validity-scaling-for-llm-metacognitive-self-report | Route /paper/before-you-interpret-the-profile-validity-scaling-for-llm-metacognitive-self-report
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/before-you-interpret-the-profile-validity-scaling-for-llm-metacognitive-self-reportMCP example
{
"tool": "get_paper",
"arguments": {
"arxiv_id": "2604.17707"
}
}source_context
{
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"query": "Before You Interpret the Profile: Validity Scaling for LLM Metacognitive Self-Report",
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"topic_slug": null,
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}Paper proof page receipt window
/buildability/before-you-interpret-the-profile-validity-scaling-for-llm-metacognitive-self-report
Subject: Before You Interpret the Profile: Validity Scaling for LLM Metacognitive Self-Report
Verdict
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Dimensions overall score 7.0
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This equation captures one of the core mathematical components of the system. invalid-profile models do not (d = 2.17, p = .001). Fourth, chain-of-thought training produces two
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Receipt path
/buildability/before-you-interpret-the-profile-validity-scaling-for-llm-metacognitive-self-report
Paper ref
before-you-interpret-the-profile-validity-scaling-for-llm-metacognitive-self-report
arXiv id
2604.17707
Generated at
2026-04-21T20:33:50.946Z
Evidence freshness
stale
Last verification
2026-04-21T20:33:50.946Z
Sources
4
References
0
Coverage
83%
Lineage hash
0a7d772906085671ec4a80f81dfa20f5a4a0055531e5d809db9e763c1ed87c72
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not_verified
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Pending verification refs / 4 sources / Verification pending
references
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This equation captures one of the core mathematical components of the system. α = .953. Split-half reliability ranges from r = .914 to .979 across tracks (Spearman-Brown corrected
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This equation defines the score or evaluation function that determines model quality.
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