Math Education Digital Shadows for facilitating learning with LLMs: Math performance, anxiety and confidence in simulated students and AIs explores A dataset mapping LLM mathematical reasoning, anxiety, and confidence across simulated student and AI personas.. Commercial viability score: 4/10 in AI Education.
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This route is the stable paper-level surface for citations, viability, references, and downstream handoffs. Use it as the proof layer behind Signal Canvas, workspace creation, and launch-pack generation.
Page Freshness
Canonical route: /paper/math-education-digital-shadows-for-facilitating-learning-with-llms-math-performance-anxiety-and-confidence-in-simulated
Page-specific freshness sourced from this paper's evidence receipt and score bundle.
Agent Handoff
Canonical ID math-education-digital-shadows-for-facilitating-learning-with-llms-math-performance-anxiety-and-confidence-in-simulated | Route /paper/math-education-digital-shadows-for-facilitating-learning-with-llms-math-performance-anxiety-and-confidence-in-simulated
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/math-education-digital-shadows-for-facilitating-learning-with-llms-math-performance-anxiety-and-confidence-in-simulatedMCP example
{
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"arguments": {
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}
}source_context
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}Paper proof page receipt window
/buildability/math-education-digital-shadows-for-facilitating-learning-with-llms-math-performance-anxiety-and-confidence-in-simulated
Subject: Math Education Digital Shadows for facilitating learning with LLMs: Math performance, anxiety and confidence in simulated students and AIs
Verdict
Ignore
Verdict is Ignore because current viability and proof state do not clear the buildability gate.
Time to first demo
Insufficient data
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Structured compute envelope
Insufficient data
No data, compute, hardware, memory, latency, dependency, or serving requirement receipt is attached.
Constellation, claims, and market context stay visible on the paper proof page even when commercialization rails are held back for incomplete proof receipts.
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Preparing verified analysis
Dimensions overall score 4.0
Visual citation anchors from the paper document graph.
Owned Distribution
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Receipt path
/buildability/math-education-digital-shadows-for-facilitating-learning-with-llms-math-performance-anxiety-and-confidence-in-simulated
Paper ref
math-education-digital-shadows-for-facilitating-learning-with-llms-math-performance-anxiety-and-confidence-in-simulated
arXiv id
2604.27618
Generated at
2026-05-01T15:05:30.597Z
Evidence freshness
fresh
Last verification
2026-05-01T15:05:30.597Z
Sources
3
References
0
Coverage
50%
Lineage hash
d3beec83e7f2e845c32eb5310be46078fb36404cee28b6ef543706b2fb195846
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. T = 0.85, T = 0.90 and T = 0.95 and selected the threshold that identified the most similarities. Having selected a valu
Page and bbox are available; crop image is pending.
This equation captures one of the core mathematical components of the system. differed across LLMs, ranging from ≈1% (DeepSeek Chat) to a maximum of ≈55% (Granite 4 Tiny).
Page and bbox are available; crop image is pending.
This equation defines the score or evaluation function that determines model quality.
Page and bbox are available; crop image is pending.
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