{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:CFCPUSAQHGRQHMZZBFE7TBNB7T","short_pith_number":"pith:CFCPUSAQ","schema_version":"1.0","canonical_sha256":"1144fa481039a303b3390949f985a1fcc15d5c291e56b6792fb05c8dfa87ecf2","source":{"kind":"arxiv","id":"1901.07948","version":1},"attestation_state":"computed","paper":{"title":"Self-avoiding walks and connective constants in clustered scale-free networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cond-mat.stat-mech"],"primary_cat":"cond-mat.dis-nn","authors_text":"Carlos P. Herrero","submitted_at":"2019-01-23T15:27:03Z","abstract_excerpt":"Various types of walks on complex networks have been used in recent years to model search and navigation in several kinds of systems, with particular emphasis on random walks. This gives valuable information on network properties, but self-avoiding walks (SAWs) may be more suitable than unrestricted random walks to study long-distance characteristics of complex systems. Here we study SAWs in clustered scale-free networks, characterized by a degree distribution of the form $P(k) \\sim k^{-\\gamma}$ for large $k$. Clustering is introduced in these networks by inserting three-node loops (triangles)"},"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":"1901.07948","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.dis-nn","submitted_at":"2019-01-23T15:27:03Z","cross_cats_sorted":["cond-mat.stat-mech"],"title_canon_sha256":"f9a8ade246d5c3cecbfe7470f070297dc56161132473be2273e2c2fd61acc5e8","abstract_canon_sha256":"790acd43348c68e464ad512b6b0c62992cdba49d070405a85e832fad53ef32cb"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:55:39.436919Z","signature_b64":"I6xfNWuWCwTiJg3FX6bTXvch6pcM/7XIYFhcEfxKhRkUxrfZDBePZp4lYWFDxE3fc/uwI+S2TPJDLZcR8w8GBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1144fa481039a303b3390949f985a1fcc15d5c291e56b6792fb05c8dfa87ecf2","last_reissued_at":"2026-05-17T23:55:39.436423Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:55:39.436423Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Self-avoiding walks and connective constants in clustered scale-free networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cond-mat.stat-mech"],"primary_cat":"cond-mat.dis-nn","authors_text":"Carlos P. Herrero","submitted_at":"2019-01-23T15:27:03Z","abstract_excerpt":"Various types of walks on complex networks have been used in recent years to model search and navigation in several kinds of systems, with particular emphasis on random walks. This gives valuable information on network properties, but self-avoiding walks (SAWs) may be more suitable than unrestricted random walks to study long-distance characteristics of complex systems. Here we study SAWs in clustered scale-free networks, characterized by a degree distribution of the form $P(k) \\sim k^{-\\gamma}$ for large $k$. Clustering is introduced in these networks by inserting three-node loops (triangles)"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.07948","kind":"arxiv","version":1},"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":"1901.07948","created_at":"2026-05-17T23:55:39.436509+00:00"},{"alias_kind":"arxiv_version","alias_value":"1901.07948v1","created_at":"2026-05-17T23:55:39.436509+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.07948","created_at":"2026-05-17T23:55:39.436509+00:00"},{"alias_kind":"pith_short_12","alias_value":"CFCPUSAQHGRQ","created_at":"2026-05-18T12:33:12.712433+00:00"},{"alias_kind":"pith_short_16","alias_value":"CFCPUSAQHGRQHMZZ","created_at":"2026-05-18T12:33:12.712433+00:00"},{"alias_kind":"pith_short_8","alias_value":"CFCPUSAQ","created_at":"2026-05-18T12:33:12.712433+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/CFCPUSAQHGRQHMZZBFE7TBNB7T","json":"https://pith.science/pith/CFCPUSAQHGRQHMZZBFE7TBNB7T.json","graph_json":"https://pith.science/api/pith-number/CFCPUSAQHGRQHMZZBFE7TBNB7T/graph.json","events_json":"https://pith.science/api/pith-number/CFCPUSAQHGRQHMZZBFE7TBNB7T/events.json","paper":"https://pith.science/paper/CFCPUSAQ"},"agent_actions":{"view_html":"https://pith.science/pith/CFCPUSAQHGRQHMZZBFE7TBNB7T","download_json":"https://pith.science/pith/CFCPUSAQHGRQHMZZBFE7TBNB7T.json","view_paper":"https://pith.science/paper/CFCPUSAQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1901.07948&json=true","fetch_graph":"https://pith.science/api/pith-number/CFCPUSAQHGRQHMZZBFE7TBNB7T/graph.json","fetch_events":"https://pith.science/api/pith-number/CFCPUSAQHGRQHMZZBFE7TBNB7T/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CFCPUSAQHGRQHMZZBFE7TBNB7T/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CFCPUSAQHGRQHMZZBFE7TBNB7T/action/storage_attestation","attest_author":"https://pith.science/pith/CFCPUSAQHGRQHMZZBFE7TBNB7T/action/author_attestation","sign_citation":"https://pith.science/pith/CFCPUSAQHGRQHMZZBFE7TBNB7T/action/citation_signature","submit_replication":"https://pith.science/pith/CFCPUSAQHGRQHMZZBFE7TBNB7T/action/replication_record"}},"created_at":"2026-05-17T23:55:39.436509+00:00","updated_at":"2026-05-17T23:55:39.436509+00:00"}