Pith Number
pith:JWTGQBOA
pith:2026:JWTGQBOAYYAWSH33XM7RWYPDH6
not attested
not anchored
not stored
refs pending
Multi-Modal Machine Learning for Population- and Subject-Specific lncRNA-Type 2 Diabetes Association Analysis
arxiv:2605.20747 v1 · 2026-05-20 · q-bio.GN
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{JWTGQBOAYYAWSH33XM7RWYPDH6}
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 | 2026-05-21T01:04:52.052355Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
4da66805c0c601691f7bbb3f1b61e33fa24ed5ba225427b79b1e0a4b0e0f4372
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/JWTGQBOAYYAWSH33XM7RWYPDH6 \
| 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: 4da66805c0c601691f7bbb3f1b61e33fa24ed5ba225427b79b1e0a4b0e0f4372
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "1108b01bf6ca170b0b2c0496d4edd8380624d1b9e5136bd24f7ea93373e7f785",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
"primary_cat": "q-bio.GN",
"submitted_at": "2026-05-20T05:49:42Z",
"title_canon_sha256": "35b1536a73df2837dc0201651d3005e803ff1b80e3893ae57224771ad2822f7b"
},
"schema_version": "1.0",
"source": {
"id": "2605.20747",
"kind": "arxiv",
"version": 1
}
}