Buildability / Receipt
This public receipt window renders only fields present in the canonical receipt object, deterministic fixture receipt, or canonical evidence receipt. Missing compute, demo, hash, signature, approval, telemetry, and adoption fields stay explicit.
Public buildability page receipt window
/buildability/how-fast-should-a-model-commit-to-supervision-training-reasoning-models-on-the-tsallis-loss-continuum
Subject: How Fast Should a Model Commit to Supervision? Training Reasoning Models on the Tsallis Loss Continuum
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
No first-demo timestamp, owner estimate, or elapsed demo receipt is attached to this surface.
Data
{"file name": "input.pdf", "number of pages": 29, "author": "Chu-Cheng Lin; Eugene Ie"
Truth Boundary
Buildability surfaces only report computed viability and proof receipts. They do not claim live production usage, pilot outcomes, founder sign-off, public Brier calibration, judge divergence, or external adoption unless explicitly sourced.
Compute
{"file name": "input.pdf", "number of pages": 29, "author": "Chu-Cheng Lin; Eugene Ie", "title": "How Fast Should a Model Commit to Supervision? Training Reasoning Models on the Tsallis Loss Continuum", "creation date": null, "modification date": null, "kids": []}
Inference
{"file name": "input.pdf", "number of pages": 29, "author": "Chu-Cheng Lin; Eugene Ie", "title": "How Fast Should a Model Commit to Supervision? Training Reasoning Models on the Tsallis Loss Continuum", "creation date": null, "modification date": null, "kids": []}
Hardware
{"file name": "input.pdf", "number of pages": 29, "author": "Chu-Cheng Lin; Eugene Ie", "title": "How Fast Should a Model Commit to Supervision? Training Reasoning Models on the Tsallis Loss Continuum", "creation date": null, "modification date": null, "kids": []}
Receipt path
/buildability/how-fast-should-a-model-commit-to-supervision-training-reasoning-models-on-the-tsallis-loss-continuum
Paper ref
how-fast-should-a-model-commit-to-supervision-training-reasoning-models-on-the-tsallis-loss-continuum
arXiv id
2604.25907
Generated at
2026-04-29T03:18:05.212Z
Evidence freshness
stale
Last verification
2026-04-29T03:18:05.212Z
Sources
3
References
0
Coverage
50%
Lineage hash
8a832e20d70bdd4093f831888362aa0d1862e2b24edf908e5f942aec5cd796c3
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.
Some score or evidence fields are outside the preferred freshness window.
repo_url
references