Pith Number
pith:2H5U5M5R
pith:2022:2H5U5M5R6SB2V75CQSDS5D2L64
not attested
not anchored
not stored
refs pending
Temperature Field Inversion of Heat-Source Systems via Physics-Informed Neural Networks
arxiv:2201.06880 v1 · 2022-01-18 · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{2H5U5M5R6SB2V75CQSDS5D2L64}
Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge
Record completeness
1
Bitcoin timestamp
2
Internet Archive
3
Author claim
· sign in to
claim
4
Citations
5
Replications
✓
Portable graph bundle live · download bundle · merged
state
The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same
current state with the deterministic merge algorithm.
Receipt and verification
| First computed | 2026-07-05T04:30:54.567707Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
d1fb4eb3b1f483aaffa284872e8f4bf702d416c5266a64a9fcc0bd9eabccb0f8
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/2H5U5M5R6SB2V75CQSDS5D2L64 \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: d1fb4eb3b1f483aaffa284872e8f4bf702d416c5266a64a9fcc0bd9eabccb0f8
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "dfee5c06a26eb23f3e7026a22562fe933329e4cac6436688ddbecbd2dbd3b81e",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2022-01-18T11:21:35Z",
"title_canon_sha256": "194a93dc6bf7d6386a3c3b211622832c490537ca611765da7e7a020f23272c29"
},
"schema_version": "1.0",
"source": {
"id": "2201.06880",
"kind": "arxiv",
"version": 1
}
}