Pith Number
pith:OBKXTT2M
pith:2019:OBKXTT2M3A27UUG4UWLJJYBCSB
not attested
not anchored
not stored
refs pending
Spatio-Temporal Convolutional LSTMs for Tumor Growth Prediction by Learning 4D Longitudinal Patient Data
arxiv:1902.08716 v2 · 2019-02-23 · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{OBKXTT2M3A27UUG4UWLJJYBCSB}
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 | 2026-07-05T00:06:21.255185Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
705579cf4cd835fa50dca59694e02290470f6ed47431a16d76fdd0d8d4b995b1
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/OBKXTT2M3A27UUG4UWLJJYBCSB \
| 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: 705579cf4cd835fa50dca59694e02290470f6ed47431a16d76fdd0d8d4b995b1
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "10e338e22c9aa35159803f0ce237dcc48a1b526f5abee5eb94196d6b420e8831",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CV",
"submitted_at": "2019-02-23T02:05:50Z",
"title_canon_sha256": "c1d959fdcf4fcdfd6acc5b5eb9fd0d3e44db104c96f01042bab9c7712c1cca0f"
},
"schema_version": "1.0",
"source": {
"id": "1902.08716",
"kind": "arxiv",
"version": 2
}
}