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/noise-aware-visual-representation-learning-for-medical-visual-question-answering
Subject: Noise-Aware Visual Representation Learning for Medical Visual Question Answering
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": 15, "author": "I Putu Adi Pratama; Bahadorreza Ofoghi; Atul Sajjanhar; Shang Gao"
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": 15, "author": "I Putu Adi Pratama; Bahadorreza Ofoghi; Atul Sajjanhar; Shang Gao", "title": "Noise-Aware Visual Representation Learning for Medical Visual Question Answering", "creation date": null, "modification date": null, "kids": []}
Inference
{"file name": "input.pdf", "number of pages": 15, "author": "I Putu Adi Pratama; Bahadorreza Ofoghi; Atul Sajjanhar; Shang Gao", "title": "Noise-Aware Visual Representation Learning for Medical Visual Question Answering", "creation date": null, "modification date": null, "kids": []}
Hardware
{"file name": "input.pdf", "number of pages": 15, "author": "I Putu Adi Pratama; Bahadorreza Ofoghi; Atul Sajjanhar; Shang Gao", "title": "Noise-Aware Visual Representation Learning for Medical Visual Question Answering", "creation date": null, "modification date": null, "kids": []}
Receipt path
/buildability/noise-aware-visual-representation-learning-for-medical-visual-question-answering
Paper ref
noise-aware-visual-representation-learning-for-medical-visual-question-answering
arXiv id
2606.05535
Generated at
2026-06-06T03:22:48.789Z
Evidence freshness
fresh
Last verification
2026-06-06T03:22:48.789Z
Sources
3
References
0
Coverage
50%
Lineage hash
9f9967b2f51a05a485e5bcd59a4112ff1deefe253446f6dc8fc1878d98f555be
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