From Phenomenological Fitting to Endogenous Deduction: A Paradigm Leap via Meta-Principle Physics Architecture explores A Meta-Principle Physics Architecture that embeds core physical principles like connectivity, conservation, and periodicity into neural networks for improved physical reasoning and generalization.. Commercial viability score: 3/10 in AI for Science.
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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/from-phenomenological-fitting-to-endogenous-deduction-a-paradigm-leap-via-meta-principle-physics-architecture
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Agent Handoff
Canonical ID from-phenomenological-fitting-to-endogenous-deduction-a-paradigm-leap-via-meta-principle-physics-architecture | Route /paper/from-phenomenological-fitting-to-endogenous-deduction-a-paradigm-leap-via-meta-principle-physics-architecture
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/from-phenomenological-fitting-to-endogenous-deduction-a-paradigm-leap-via-meta-principle-physics-architectureMCP example
{
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"arguments": {
"arxiv_id": "2604.08245"
}
}source_context
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}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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