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/self-paced-curriculum-reinforcement-learning-for-autonomous-superbike-racing-in-simulation
Subject: Self-Paced Curriculum Reinforcement Learning for Autonomous Superbike Racing in Simulation
Verdict
Ignore
Verdict is Ignore because current viability and proof state do not clear the buildability gate.
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": 4, "author": "Luca Ghisi; Jacopo Essenziale; Carlo D'Eramo; Matteo Luperto"
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": 4, "author": "Luca Ghisi; Jacopo Essenziale; Carlo D'Eramo; Matteo Luperto", "title": "Self-Paced Curriculum Reinforcement Learning for Autonomous Superbike Racing in Simulation", "creation date": null, "modification date": null, "kids": []}
Inference
{"file name": "input.pdf", "number of pages": 4, "author": "Luca Ghisi; Jacopo Essenziale; Carlo D'Eramo; Matteo Luperto", "title": "Self-Paced Curriculum Reinforcement Learning for Autonomous Superbike Racing in Simulation", "creation date": null, "modification date": null, "kids": []}
Hardware
{"file name": "input.pdf", "number of pages": 4, "author": "Luca Ghisi; Jacopo Essenziale; Carlo D'Eramo; Matteo Luperto", "title": "Self-Paced Curriculum Reinforcement Learning for Autonomous Superbike Racing in Simulation", "creation date": null, "modification date": null, "kids": []}
Receipt path
/buildability/self-paced-curriculum-reinforcement-learning-for-autonomous-superbike-racing-in-simulation
Paper ref
self-paced-curriculum-reinforcement-learning-for-autonomous-superbike-racing-in-simulation
arXiv id
2606.09236
Generated at
2026-06-09T03:25:47.654Z
Evidence freshness
fresh
Last verification
2026-06-09T03:25:47.654Z
Sources
3
References
0
Coverage
50%
Lineage hash
4d68828e4c434cac514ab87d48d728edb9d1aadd2105d26ee63d21f185a874ee
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.
Canonical opportunity-kernel evidence is available for this receipt window.
repo_url
references