{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:UNJIR2A4SVB6OIYUSQXPE3S4PE","short_pith_number":"pith:UNJIR2A4","schema_version":"1.0","canonical_sha256":"a35288e81c9543e72314942ef26e5c791f8f40de3e18d10a11d442a5c3b61c5e","source":{"kind":"arxiv","id":"1510.08542","version":2},"attestation_state":"computed","paper":{"title":"Multi-scale structure and topological anomaly detection via a new network statistic: The onion decomposition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cond-mat.dis-nn","cs.DM","cs.SI","math.CO"],"primary_cat":"physics.soc-ph","authors_text":"Antoine Allard, Joshua A. Grochow, Laurent H\\'ebert-Dufresne","submitted_at":"2015-10-29T01:59:06Z","abstract_excerpt":"We introduce a new network statistic that measures diverse structural properties at the micro-, meso-, and macroscopic scales, while still being easy to compute and easy to interpret at a glance. Our statistic, the onion spectrum, is based on the onion decomposition, which refines the k-core decomposition, a standard network fingerprinting method. The onion spectrum is exactly as easy to compute as the k-cores: It is based on the stages at which each vertex gets removed from a graph in the standard algorithm for computing the k-cores. But the onion spectrum reveals much more information about "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1510.08542","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.soc-ph","submitted_at":"2015-10-29T01:59:06Z","cross_cats_sorted":["cond-mat.dis-nn","cs.DM","cs.SI","math.CO"],"title_canon_sha256":"a543bf3c3ae08bb8bbd5b8c33fd1b102f9be9928a6a0c6f54ccd4a14a25a96b5","abstract_canon_sha256":"0c536eb4ed3c99522a40e435cce9afac183852ddc6728fb49df47abcce8b6805"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:49:34.829239Z","signature_b64":"Llawckr+vVl8rR6yH7GqN6DdbOQkMFbdn/vRzzQMqvyoeSLc/mEF6HfsNcA2P2XamWnoUB0QFHcceF946K1RBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a35288e81c9543e72314942ef26e5c791f8f40de3e18d10a11d442a5c3b61c5e","last_reissued_at":"2026-05-18T00:49:34.828810Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:49:34.828810Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Multi-scale structure and topological anomaly detection via a new network statistic: The onion decomposition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cond-mat.dis-nn","cs.DM","cs.SI","math.CO"],"primary_cat":"physics.soc-ph","authors_text":"Antoine Allard, Joshua A. Grochow, Laurent H\\'ebert-Dufresne","submitted_at":"2015-10-29T01:59:06Z","abstract_excerpt":"We introduce a new network statistic that measures diverse structural properties at the micro-, meso-, and macroscopic scales, while still being easy to compute and easy to interpret at a glance. Our statistic, the onion spectrum, is based on the onion decomposition, which refines the k-core decomposition, a standard network fingerprinting method. The onion spectrum is exactly as easy to compute as the k-cores: It is based on the stages at which each vertex gets removed from a graph in the standard algorithm for computing the k-cores. But the onion spectrum reveals much more information about "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1510.08542","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1510.08542","created_at":"2026-05-18T00:49:34.828879+00:00"},{"alias_kind":"arxiv_version","alias_value":"1510.08542v2","created_at":"2026-05-18T00:49:34.828879+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1510.08542","created_at":"2026-05-18T00:49:34.828879+00:00"},{"alias_kind":"pith_short_12","alias_value":"UNJIR2A4SVB6","created_at":"2026-05-18T12:29:44.643036+00:00"},{"alias_kind":"pith_short_16","alias_value":"UNJIR2A4SVB6OIYU","created_at":"2026-05-18T12:29:44.643036+00:00"},{"alias_kind":"pith_short_8","alias_value":"UNJIR2A4","created_at":"2026-05-18T12:29:44.643036+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/UNJIR2A4SVB6OIYUSQXPE3S4PE","json":"https://pith.science/pith/UNJIR2A4SVB6OIYUSQXPE3S4PE.json","graph_json":"https://pith.science/api/pith-number/UNJIR2A4SVB6OIYUSQXPE3S4PE/graph.json","events_json":"https://pith.science/api/pith-number/UNJIR2A4SVB6OIYUSQXPE3S4PE/events.json","paper":"https://pith.science/paper/UNJIR2A4"},"agent_actions":{"view_html":"https://pith.science/pith/UNJIR2A4SVB6OIYUSQXPE3S4PE","download_json":"https://pith.science/pith/UNJIR2A4SVB6OIYUSQXPE3S4PE.json","view_paper":"https://pith.science/paper/UNJIR2A4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1510.08542&json=true","fetch_graph":"https://pith.science/api/pith-number/UNJIR2A4SVB6OIYUSQXPE3S4PE/graph.json","fetch_events":"https://pith.science/api/pith-number/UNJIR2A4SVB6OIYUSQXPE3S4PE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/UNJIR2A4SVB6OIYUSQXPE3S4PE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/UNJIR2A4SVB6OIYUSQXPE3S4PE/action/storage_attestation","attest_author":"https://pith.science/pith/UNJIR2A4SVB6OIYUSQXPE3S4PE/action/author_attestation","sign_citation":"https://pith.science/pith/UNJIR2A4SVB6OIYUSQXPE3S4PE/action/citation_signature","submit_replication":"https://pith.science/pith/UNJIR2A4SVB6OIYUSQXPE3S4PE/action/replication_record"}},"created_at":"2026-05-18T00:49:34.828879+00:00","updated_at":"2026-05-18T00:49:34.828879+00:00"}