Pith Number
pith:2TPVBTYI
pith:2026:2TPVBTYI7NNRVSIR7JWTNBYGGN
not attested
not anchored
not stored
refs pending
Discovering Functionally Selective Brain Regions with a Deep Topographic Multimodal Model
arxiv:2606.09770 v1 · 2026-06-08 · q-bio.NC · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{2TPVBTYI7NNRVSIR7JWTNBYGGN}
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 | 2026-06-09T02:09:08.767999Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
d4df50cf08fb5b1ac911fa6d36870633657db34aa6aa2ad49f3e90db0d3eb61d
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/2TPVBTYI7NNRVSIR7JWTNBYGGN \
| 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: d4df50cf08fb5b1ac911fa6d36870633657db34aa6aa2ad49f3e90db0d3eb61d
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "2299fea9160b2a5cec37ebaec5475a6976503bc22ef022e69543fed3218999c7",
"cross_cats_sorted": [
"cs.LG"
],
"license": "http://creativecommons.org/licenses/by-sa/4.0/",
"primary_cat": "q-bio.NC",
"submitted_at": "2026-06-08T17:31:50Z",
"title_canon_sha256": "c89d7bffceef355d37a7336180ca8a806ee9ce0de4c94c38821287165b173454"
},
"schema_version": "1.0",
"source": {
"id": "2606.09770",
"kind": "arxiv",
"version": 1
}
}