Pith Number
pith:MS5JPN4M
pith:2017:MS5JPN4MT6Y3JWQ32HH63CE5DN
not attested
not anchored
not stored
refs pending
Hierarchical modeling of molecular energies using a deep neural network
arxiv:1710.00017 v1 · 2017-09-29 · stat.ML · physics.chem-ph
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{MS5JPN4MT6Y3JWQ32HH63CE5DN}
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
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claim
4
Citations
5
Replications
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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 | 2026-05-18T00:19:26.503628Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
64ba97b78c9fb1b4da1bd1cfed889d1b7c123abf2bcb30f62578f585858cf5df
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/MS5JPN4MT6Y3JWQ32HH63CE5DN \
| 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: 64ba97b78c9fb1b4da1bd1cfed889d1b7c123abf2bcb30f62578f585858cf5df
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "b8fdeec2820a2dec45e71bee9791de7d6390cec49b2b5425ba091c32fc743916",
"cross_cats_sorted": [
"physics.chem-ph"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "stat.ML",
"submitted_at": "2017-09-29T18:12:29Z",
"title_canon_sha256": "3ab90e281ddcf17b0fa2f19e76c8a62d7bed98f6c5f410b30622e255a73bef95"
},
"schema_version": "1.0",
"source": {
"id": "1710.00017",
"kind": "arxiv",
"version": 1
}
}