{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:Y2K427KBZ4FZZ7NKN3XEQVSKMO","short_pith_number":"pith:Y2K427KB","canonical_record":{"source":{"id":"1803.01616","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"physics.soc-ph","submitted_at":"2018-03-05T11:48:13Z","cross_cats_sorted":["cs.SI","physics.data-an","q-bio.MN","stat.ML"],"title_canon_sha256":"eeca8838fe288f635ebc21347de14187af76777d06172fadb613dea247b4cad6","abstract_canon_sha256":"a047dbe40202db2720eae03f3c2415cb7032b5c1dd5c6d971d09ab7d1a590d6e"},"schema_version":"1.0"},"canonical_sha256":"c695cd7d41cf0b9cfdaa6eee48564a63ad9e808169a17cdce73590f4f1b479af","source":{"kind":"arxiv","id":"1803.01616","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1803.01616","created_at":"2026-05-17T23:49:44Z"},{"alias_kind":"arxiv_version","alias_value":"1803.01616v1","created_at":"2026-05-17T23:49:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.01616","created_at":"2026-05-17T23:49:44Z"},{"alias_kind":"pith_short_12","alias_value":"Y2K427KBZ4FZ","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_16","alias_value":"Y2K427KBZ4FZZ7NK","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_8","alias_value":"Y2K427KB","created_at":"2026-05-18T12:33:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:Y2K427KBZ4FZZ7NKN3XEQVSKMO","target":"record","payload":{"canonical_record":{"source":{"id":"1803.01616","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"physics.soc-ph","submitted_at":"2018-03-05T11:48:13Z","cross_cats_sorted":["cs.SI","physics.data-an","q-bio.MN","stat.ML"],"title_canon_sha256":"eeca8838fe288f635ebc21347de14187af76777d06172fadb613dea247b4cad6","abstract_canon_sha256":"a047dbe40202db2720eae03f3c2415cb7032b5c1dd5c6d971d09ab7d1a590d6e"},"schema_version":"1.0"},"canonical_sha256":"c695cd7d41cf0b9cfdaa6eee48564a63ad9e808169a17cdce73590f4f1b479af","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:49:44.021286Z","signature_b64":"zBV8n+bG/qMqwdONHiyp74kBYyD/0mdsz1lzLyluoTBXgv3qihh0Eonq1OJgXlNy+tLIPFcYusE4DE4qJxGEAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c695cd7d41cf0b9cfdaa6eee48564a63ad9e808169a17cdce73590f4f1b479af","last_reissued_at":"2026-05-17T23:49:44.020637Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:49:44.020637Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1803.01616","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:49:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fFgEF/TZHaUz9vEylGaPCRD2WG0bRYPRvH/qWmG3uVmYIEMsgF4nxQt01/NQEr8yhGq0FsfKHV08qTHxGmHbAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T22:43:48.555600Z"},"content_sha256":"1218dcc797f7e8dba8e870bcf3f3505cd4539b14b4d385a54d12459c9f168117","schema_version":"1.0","event_id":"sha256:1218dcc797f7e8dba8e870bcf3f3505cd4539b14b4d385a54d12459c9f168117"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:Y2K427KBZ4FZZ7NKN3XEQVSKMO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Tensorial and bipartite block models for link prediction in layered networks and temporal networks","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.SI","physics.data-an","q-bio.MN","stat.ML"],"primary_cat":"physics.soc-ph","authors_text":"Antonia Godoy-Lorite, Marc Tarres-Deulofeu, Marta Sales-Pardo, Roger Guimera","submitted_at":"2018-03-05T11:48:13Z","abstract_excerpt":"Many real-world complex systems are well represented as multilayer networks; predicting interactions in those systems is one of the most pressing problems in predictive network science. To address this challenge, we introduce two stochastic block models for multilayer and temporal networks; one of them uses nodes as its fundamental unit, whereas the other focuses on links. We also develop scalable algorithms for inferring the parameters of these models. Because our models describe all layers simultaneously, our approach takes full advantage of the information contained in the whole network whe"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.01616","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:49:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WRy099c+8lIkm/NCPvMgIjAPbY4zl6xtsJupE/ycoc0DuDLo+5n2sOI8+dwh3n/9auv+Iz6ikVBDwp6+UlzRBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T22:43:48.556246Z"},"content_sha256":"fb2f9252f077eb344abd5fd6708eb19ad86c5b91d6ad83519ca60ec258e26c5d","schema_version":"1.0","event_id":"sha256:fb2f9252f077eb344abd5fd6708eb19ad86c5b91d6ad83519ca60ec258e26c5d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Y2K427KBZ4FZZ7NKN3XEQVSKMO/bundle.json","state_url":"https://pith.science/pith/Y2K427KBZ4FZZ7NKN3XEQVSKMO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Y2K427KBZ4FZZ7NKN3XEQVSKMO/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-06T22:43:48Z","links":{"resolver":"https://pith.science/pith/Y2K427KBZ4FZZ7NKN3XEQVSKMO","bundle":"https://pith.science/pith/Y2K427KBZ4FZZ7NKN3XEQVSKMO/bundle.json","state":"https://pith.science/pith/Y2K427KBZ4FZZ7NKN3XEQVSKMO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Y2K427KBZ4FZZ7NKN3XEQVSKMO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:Y2K427KBZ4FZZ7NKN3XEQVSKMO","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"a047dbe40202db2720eae03f3c2415cb7032b5c1dd5c6d971d09ab7d1a590d6e","cross_cats_sorted":["cs.SI","physics.data-an","q-bio.MN","stat.ML"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"physics.soc-ph","submitted_at":"2018-03-05T11:48:13Z","title_canon_sha256":"eeca8838fe288f635ebc21347de14187af76777d06172fadb613dea247b4cad6"},"schema_version":"1.0","source":{"id":"1803.01616","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1803.01616","created_at":"2026-05-17T23:49:44Z"},{"alias_kind":"arxiv_version","alias_value":"1803.01616v1","created_at":"2026-05-17T23:49:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.01616","created_at":"2026-05-17T23:49:44Z"},{"alias_kind":"pith_short_12","alias_value":"Y2K427KBZ4FZ","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_16","alias_value":"Y2K427KBZ4FZZ7NK","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_8","alias_value":"Y2K427KB","created_at":"2026-05-18T12:33:04Z"}],"graph_snapshots":[{"event_id":"sha256:fb2f9252f077eb344abd5fd6708eb19ad86c5b91d6ad83519ca60ec258e26c5d","target":"graph","created_at":"2026-05-17T23:49:44Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Many real-world complex systems are well represented as multilayer networks; predicting interactions in those systems is one of the most pressing problems in predictive network science. To address this challenge, we introduce two stochastic block models for multilayer and temporal networks; one of them uses nodes as its fundamental unit, whereas the other focuses on links. We also develop scalable algorithms for inferring the parameters of these models. Because our models describe all layers simultaneously, our approach takes full advantage of the information contained in the whole network whe","authors_text":"Antonia Godoy-Lorite, Marc Tarres-Deulofeu, Marta Sales-Pardo, Roger Guimera","cross_cats":["cs.SI","physics.data-an","q-bio.MN","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"physics.soc-ph","submitted_at":"2018-03-05T11:48:13Z","title":"Tensorial and bipartite block models for link prediction in layered networks and temporal networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.01616","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:1218dcc797f7e8dba8e870bcf3f3505cd4539b14b4d385a54d12459c9f168117","target":"record","created_at":"2026-05-17T23:49:44Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"a047dbe40202db2720eae03f3c2415cb7032b5c1dd5c6d971d09ab7d1a590d6e","cross_cats_sorted":["cs.SI","physics.data-an","q-bio.MN","stat.ML"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"physics.soc-ph","submitted_at":"2018-03-05T11:48:13Z","title_canon_sha256":"eeca8838fe288f635ebc21347de14187af76777d06172fadb613dea247b4cad6"},"schema_version":"1.0","source":{"id":"1803.01616","kind":"arxiv","version":1}},"canonical_sha256":"c695cd7d41cf0b9cfdaa6eee48564a63ad9e808169a17cdce73590f4f1b479af","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c695cd7d41cf0b9cfdaa6eee48564a63ad9e808169a17cdce73590f4f1b479af","first_computed_at":"2026-05-17T23:49:44.020637Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:49:44.020637Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zBV8n+bG/qMqwdONHiyp74kBYyD/0mdsz1lzLyluoTBXgv3qihh0Eonq1OJgXlNy+tLIPFcYusE4DE4qJxGEAA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:49:44.021286Z","signed_message":"canonical_sha256_bytes"},"source_id":"1803.01616","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1218dcc797f7e8dba8e870bcf3f3505cd4539b14b4d385a54d12459c9f168117","sha256:fb2f9252f077eb344abd5fd6708eb19ad86c5b91d6ad83519ca60ec258e26c5d"],"state_sha256":"b0186c4ca692606b7bfa9a85f26132debeef33d85af01932cc1f90768040d126"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GJe7xwP1ANBAZZwlDtYZgmgd6lYaV0hgIBmuPiThuwf1jLywAke6lF2R288AXnIQWKxLSiFb9su+Sv9CtfpLDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-06T22:43:48.559598Z","bundle_sha256":"30b26a4f17cee80a12db285ec8f88a56bc14a9e66491a9988621b15d5251c57c"}}