pith:RNSR6Z4C
Evidence for a Functional Proximity Law in Multilayer Networks
In multilayer networks, hub importance persists more strongly across functionally similar layers than dissimilar ones.
arxiv:2604.23639 v2 · 2026-04-26 · cs.SI
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Claims
Hub importance scores in multilayer networks persist more strongly between functionally similar layers than dissimilar ones. We call this the Functional Proximity Law and test it across 17 pre-registered experiments.
That functional similarity between layers can be defined consistently and objectively across disparate domains and that hub importance metrics remain comparable when layers come from different data sources and measurement methods.
Hub importance scores in multilayer networks persist more strongly between functionally similar layers than dissimilar ones, supported by 17 pre-registered experiments with 9 confirmations and external validations.
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| First computed | 2026-05-26T01:02:34.334376Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
8b651f6782b299bf46a49256ffc5f425da807ba2df8aecf362db55b552bfd5fe
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/RNSR6Z4CWKM36RVESJLP7RPUEX \
| 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())"
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Canonical record JSON
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