Pith Number
pith:GLND4MMW
pith:2017:GLND4MMWZCUHHCP2ASUAOI2NVV
not attested
not anchored
not stored
refs pending
How well do experience curves predict technological progress? A method for making distributional forecasts
arxiv:1703.05979 v2 · 2017-03-17 · q-fin.EC
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{GLND4MMWZCUHHCP2ASUAOI2NVV}
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 | 2026-05-18T00:05:14.714587Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
32da3e3196c8a87389fa04a807234dad62116ae2ea5e5e33eec0aa51381a2d3f
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/GLND4MMWZCUHHCP2ASUAOI2NVV \
| 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: 32da3e3196c8a87389fa04a807234dad62116ae2ea5e5e33eec0aa51381a2d3f
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "98616c018ad5deb52105b416bc6c8911a9fce18760d5eed83f773d6bec5dcbc5",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "q-fin.EC",
"submitted_at": "2017-03-17T11:59:36Z",
"title_canon_sha256": "5e064c974145125a1213f50381ff139a4d4a85a8f9ab0bf24b284fda716c22f7"
},
"schema_version": "1.0",
"source": {
"id": "1703.05979",
"kind": "arxiv",
"version": 2
}
}