Pith Number
pith:5KM6DVDZ
pith:2019:5KM6DVDZW6GF4OXVX65L4X3YEM
not attested
not anchored
not stored
refs pending
Approximation of Riemannian Distances and Applications to Distance-Based Learning on Manifolds
arxiv:1904.11860 v1 · 2019-04-26 · math.DG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{5KM6DVDZW6GF4OXVX65L4X3YEM}
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.
Cited by
Receipt and verification
| First computed | 2026-05-17T23:47:40.773770Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
ea99e1d479b78c5e3af5bfbabe5f782337034131ef18cb8cb80d01f0f828e6cb
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/5KM6DVDZW6GF4OXVX65L4X3YEM \
| 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: ea99e1d479b78c5e3af5bfbabe5f782337034131ef18cb8cb80d01f0f828e6cb
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "da80039ec00cfb2d84eee57b89bcdc9d1063f0a40d109967ceafe414275dd42d",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "math.DG",
"submitted_at": "2019-04-26T14:17:11Z",
"title_canon_sha256": "e59f470e528c6b8a73d9de434951ddc3057f42255ffbc45dbcd85bd8f3741afd"
},
"schema_version": "1.0",
"source": {
"id": "1904.11860",
"kind": "arxiv",
"version": 1
}
}