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/a-novel-global-context-aware-deep-neural-network-for-enhanced-brain-tumor-segmentation-using-magnetic-resonance-images
Subject: A Novel Global Context-aware Deep Neural Network for Enhanced Brain Tumor Segmentation using Magnetic Resonance Images
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": 11, "author": "Sourjya Mukherjee; Ananya Bhattacharjee; R. Murugan"
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": 11, "author": "Sourjya Mukherjee; Ananya Bhattacharjee; R. Murugan", "title": "A Novel Global Context-aware Deep Neural Network for Enhanced Brain Tumor Segmentation using Magnetic Resonance Images", "creation date": null, "modification date": null, "kids": []}
Inference
{"file name": "input.pdf", "number of pages": 11, "author": "Sourjya Mukherjee; Ananya Bhattacharjee; R. Murugan", "title": "A Novel Global Context-aware Deep Neural Network for Enhanced Brain Tumor Segmentation using Magnetic Resonance Images", "creation date": null, "modification date": null, "kids": []}
Hardware
{"file name": "input.pdf", "number of pages": 11, "author": "Sourjya Mukherjee; Ananya Bhattacharjee; R. Murugan", "title": "A Novel Global Context-aware Deep Neural Network for Enhanced Brain Tumor Segmentation using Magnetic Resonance Images", "creation date": null, "modification date": null, "kids": []}
Receipt path
/buildability/a-novel-global-context-aware-deep-neural-network-for-enhanced-brain-tumor-segmentation-using-magnetic-resonance-images
Paper ref
a-novel-global-context-aware-deep-neural-network-for-enhanced-brain-tumor-segmentation-using-magnetic-resonance-images
arXiv id
2605.30510
Generated at
2026-06-01T20:25:12.723Z
Evidence freshness
stale
Last verification
2026-06-01T20:25:12.723Z
Sources
3
References
0
Coverage
50%
Lineage hash
a9bd827a773b4a52ed1e2183f73cfd02d9a9966c9f8e188712c3011acd7a0e00
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