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-neural-operator-framework-for-data-driven-discovery-of-stability-and-receptivity-in-physical-systems
Subject: A neural operator framework for data-driven discovery of stability and receptivity in physical systems
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": 30, "author": "Chengyun Wang; Liwei Chen; Nils Thuerey"
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": 30, "author": "Chengyun Wang; Liwei Chen; Nils Thuerey", "title": "A neural operator framework for data-driven discovery of stability and receptivity in physical systems", "creation date": null, "modification date": null, "kids": []}
Inference
{"file name": "input.pdf", "number of pages": 30, "author": "Chengyun Wang; Liwei Chen; Nils Thuerey", "title": "A neural operator framework for data-driven discovery of stability and receptivity in physical systems", "creation date": null, "modification date": null, "kids": []}
Hardware
{"file name": "input.pdf", "number of pages": 30, "author": "Chengyun Wang; Liwei Chen; Nils Thuerey", "title": "A neural operator framework for data-driven discovery of stability and receptivity in physical systems", "creation date": null, "modification date": null, "kids": []}
Receipt path
/buildability/a-neural-operator-framework-for-data-driven-discovery-of-stability-and-receptivity-in-physical-systems
Paper ref
a-neural-operator-framework-for-data-driven-discovery-of-stability-and-receptivity-in-physical-systems
arXiv id
2604.19465
Generated at
2026-04-22T02:13:27.071Z
Evidence freshness
stale
Last verification
2026-04-22T02:13:27.071Z
Sources
3
References
0
Coverage
50%
Lineage hash
44d6cba85b9cadd106c9e27f1f50b62329a48f8c6990287879d8703199ad87d2
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