{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:JFNFTHTLYTSOXBFXSFU5FUDGC2","short_pith_number":"pith:JFNFTHTL","schema_version":"1.0","canonical_sha256":"495a599e6bc4e4eb84b79169d2d06616ac68d0af8b83e95a11611b772392ddee","source":{"kind":"arxiv","id":"1602.07106","version":1},"attestation_state":"computed","paper":{"title":"Scalable Generation of Scale-free Graphs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC","cs.SI"],"primary_cat":"cs.DS","authors_text":"Christian Schulz, Peter Sanders","submitted_at":"2016-02-23T10:21:06Z","abstract_excerpt":"We explain how massive instances of scale-free graphs following the Barabasi-Albert model can be generated very quickly in an embarrassingly parallel way. This makes this popular model available for studying big data graph problems. As a demonstration, we generated a Petaedge graph in less than an hour."},"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":"1602.07106","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2016-02-23T10:21:06Z","cross_cats_sorted":["cs.DC","cs.SI"],"title_canon_sha256":"860fa244989c122c8be3aee399eab9a5b4f0a884d7a72c5d2907890002e79d24","abstract_canon_sha256":"0bcee0af82926ffb781a207943a1399b6981d528588362db2839347c48324c6b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:20:07.135799Z","signature_b64":"5U8yxZIGkxYrv3HKMkNBA2/IylflWIwsggyFtleiygVmCL7cujXv4gluj2dfTzLDWkw9ANK3i57+ZMV9g2i5DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"495a599e6bc4e4eb84b79169d2d06616ac68d0af8b83e95a11611b772392ddee","last_reissued_at":"2026-05-18T01:20:07.135192Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:20:07.135192Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Scalable Generation of Scale-free Graphs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC","cs.SI"],"primary_cat":"cs.DS","authors_text":"Christian Schulz, Peter Sanders","submitted_at":"2016-02-23T10:21:06Z","abstract_excerpt":"We explain how massive instances of scale-free graphs following the Barabasi-Albert model can be generated very quickly in an embarrassingly parallel way. This makes this popular model available for studying big data graph problems. As a demonstration, we generated a Petaedge graph in less than an hour."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1602.07106","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":"1602.07106","created_at":"2026-05-18T01:20:07.135269+00:00"},{"alias_kind":"arxiv_version","alias_value":"1602.07106v1","created_at":"2026-05-18T01:20:07.135269+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1602.07106","created_at":"2026-05-18T01:20:07.135269+00:00"},{"alias_kind":"pith_short_12","alias_value":"JFNFTHTLYTSO","created_at":"2026-05-18T12:30:25.849896+00:00"},{"alias_kind":"pith_short_16","alias_value":"JFNFTHTLYTSOXBFX","created_at":"2026-05-18T12:30:25.849896+00:00"},{"alias_kind":"pith_short_8","alias_value":"JFNFTHTL","created_at":"2026-05-18T12:30:25.849896+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/JFNFTHTLYTSOXBFXSFU5FUDGC2","json":"https://pith.science/pith/JFNFTHTLYTSOXBFXSFU5FUDGC2.json","graph_json":"https://pith.science/api/pith-number/JFNFTHTLYTSOXBFXSFU5FUDGC2/graph.json","events_json":"https://pith.science/api/pith-number/JFNFTHTLYTSOXBFXSFU5FUDGC2/events.json","paper":"https://pith.science/paper/JFNFTHTL"},"agent_actions":{"view_html":"https://pith.science/pith/JFNFTHTLYTSOXBFXSFU5FUDGC2","download_json":"https://pith.science/pith/JFNFTHTLYTSOXBFXSFU5FUDGC2.json","view_paper":"https://pith.science/paper/JFNFTHTL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1602.07106&json=true","fetch_graph":"https://pith.science/api/pith-number/JFNFTHTLYTSOXBFXSFU5FUDGC2/graph.json","fetch_events":"https://pith.science/api/pith-number/JFNFTHTLYTSOXBFXSFU5FUDGC2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/JFNFTHTLYTSOXBFXSFU5FUDGC2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/JFNFTHTLYTSOXBFXSFU5FUDGC2/action/storage_attestation","attest_author":"https://pith.science/pith/JFNFTHTLYTSOXBFXSFU5FUDGC2/action/author_attestation","sign_citation":"https://pith.science/pith/JFNFTHTLYTSOXBFXSFU5FUDGC2/action/citation_signature","submit_replication":"https://pith.science/pith/JFNFTHTLYTSOXBFXSFU5FUDGC2/action/replication_record"}},"created_at":"2026-05-18T01:20:07.135269+00:00","updated_at":"2026-05-18T01:20:07.135269+00:00"}