{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:L3KPQERFS3FXNP4GFT5VFMXXKZ","short_pith_number":"pith:L3KPQERF","canonical_record":{"source":{"id":"1510.03042","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2015-10-11T11:55:39Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"171215548cd85931e8ca6f038d48578874e1f159df5e60cf52d5a52cf674a55a","abstract_canon_sha256":"e274bd94a4f252b74a126a2c90e7c1293305be763b89eb026f0293665636b3bb"},"schema_version":"1.0"},"canonical_sha256":"5ed4f8122596cb76bf862cfb52b2f7567517e5bdf972f07dc727e704527e06e3","source":{"kind":"arxiv","id":"1510.03042","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1510.03042","created_at":"2026-05-18T01:30:32Z"},{"alias_kind":"arxiv_version","alias_value":"1510.03042v1","created_at":"2026-05-18T01:30:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1510.03042","created_at":"2026-05-18T01:30:32Z"},{"alias_kind":"pith_short_12","alias_value":"L3KPQERFS3FX","created_at":"2026-05-18T12:29:29Z"},{"alias_kind":"pith_short_16","alias_value":"L3KPQERFS3FXNP4G","created_at":"2026-05-18T12:29:29Z"},{"alias_kind":"pith_short_8","alias_value":"L3KPQERF","created_at":"2026-05-18T12:29:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:L3KPQERFS3FXNP4GFT5VFMXXKZ","target":"record","payload":{"canonical_record":{"source":{"id":"1510.03042","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2015-10-11T11:55:39Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"171215548cd85931e8ca6f038d48578874e1f159df5e60cf52d5a52cf674a55a","abstract_canon_sha256":"e274bd94a4f252b74a126a2c90e7c1293305be763b89eb026f0293665636b3bb"},"schema_version":"1.0"},"canonical_sha256":"5ed4f8122596cb76bf862cfb52b2f7567517e5bdf972f07dc727e704527e06e3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:30:32.885010Z","signature_b64":"/PZm+P0VvZ5tKIzYlriG20OFs6jNTMh9ltEUtkrkMNEL7Y+EqrlUvQl33q8k7lXYs57GN0GF7aAuocd33enZDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5ed4f8122596cb76bf862cfb52b2f7567517e5bdf972f07dc727e704527e06e3","last_reissued_at":"2026-05-18T01:30:32.884448Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:30:32.884448Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1510.03042","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":"2026-05-18T01:30:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Y9FvRg6sMnU36/zmkGMnm8op0+iuoStdeX3HxsyxaCb3iheJv5v399Ht6fVifpSEeL0CYwC4bXXBdEQutFTOBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T13:11:11.815038Z"},"content_sha256":"bcbbf8bd3aecde3a29b46e5488be3d9702e1167260dd9f7c3a7e959f72a6931f","schema_version":"1.0","event_id":"sha256:bcbbf8bd3aecde3a29b46e5488be3d9702e1167260dd9f7c3a7e959f72a6931f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:L3KPQERFS3FXNP4GFT5VFMXXKZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ParallelPC: an R package for efficient constraint based causal exploration","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.AI","authors_text":"Jiuyong Li, Lin Liu, Shu Hu, Tao Hoang, Thuc Duy Le","submitted_at":"2015-10-11T11:55:39Z","abstract_excerpt":"Discovering causal relationships from data is the ultimate goal of many research areas. Constraint based causal exploration algorithms, such as PC, FCI, RFCI, PC-simple, IDA and Joint-IDA have achieved significant progress and have many applications. A common problem with these methods is the high computational complexity, which hinders their applications in real world high dimensional datasets, e.g gene expression datasets. In this paper, we present an R package, ParallelPC, that includes the parallelised versions of these causal exploration algorithms. The parallelised algorithms help speed "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1510.03042","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":"2026-05-18T01:30:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3DzpliPoH7e4i9J3pMrLLvDV4aSBcERXu4wMEKr/Ha7K7g+Yk3L15iOOv90byCfE3+dG+IyAu6vu+a+GXU4tCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T13:11:11.815749Z"},"content_sha256":"598dbff8fcc23d354398c91915414c0a6df81be0673fb593a963fd36178fc32a","schema_version":"1.0","event_id":"sha256:598dbff8fcc23d354398c91915414c0a6df81be0673fb593a963fd36178fc32a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/L3KPQERFS3FXNP4GFT5VFMXXKZ/bundle.json","state_url":"https://pith.science/pith/L3KPQERFS3FXNP4GFT5VFMXXKZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/L3KPQERFS3FXNP4GFT5VFMXXKZ/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":"2026-05-30T13:11:11Z","links":{"resolver":"https://pith.science/pith/L3KPQERFS3FXNP4GFT5VFMXXKZ","bundle":"https://pith.science/pith/L3KPQERFS3FXNP4GFT5VFMXXKZ/bundle.json","state":"https://pith.science/pith/L3KPQERFS3FXNP4GFT5VFMXXKZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/L3KPQERFS3FXNP4GFT5VFMXXKZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:L3KPQERFS3FXNP4GFT5VFMXXKZ","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":"e274bd94a4f252b74a126a2c90e7c1293305be763b89eb026f0293665636b3bb","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2015-10-11T11:55:39Z","title_canon_sha256":"171215548cd85931e8ca6f038d48578874e1f159df5e60cf52d5a52cf674a55a"},"schema_version":"1.0","source":{"id":"1510.03042","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1510.03042","created_at":"2026-05-18T01:30:32Z"},{"alias_kind":"arxiv_version","alias_value":"1510.03042v1","created_at":"2026-05-18T01:30:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1510.03042","created_at":"2026-05-18T01:30:32Z"},{"alias_kind":"pith_short_12","alias_value":"L3KPQERFS3FX","created_at":"2026-05-18T12:29:29Z"},{"alias_kind":"pith_short_16","alias_value":"L3KPQERFS3FXNP4G","created_at":"2026-05-18T12:29:29Z"},{"alias_kind":"pith_short_8","alias_value":"L3KPQERF","created_at":"2026-05-18T12:29:29Z"}],"graph_snapshots":[{"event_id":"sha256:598dbff8fcc23d354398c91915414c0a6df81be0673fb593a963fd36178fc32a","target":"graph","created_at":"2026-05-18T01:30:32Z","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":"Discovering causal relationships from data is the ultimate goal of many research areas. Constraint based causal exploration algorithms, such as PC, FCI, RFCI, PC-simple, IDA and Joint-IDA have achieved significant progress and have many applications. A common problem with these methods is the high computational complexity, which hinders their applications in real world high dimensional datasets, e.g gene expression datasets. In this paper, we present an R package, ParallelPC, that includes the parallelised versions of these causal exploration algorithms. The parallelised algorithms help speed ","authors_text":"Jiuyong Li, Lin Liu, Shu Hu, Tao Hoang, Thuc Duy Le","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2015-10-11T11:55:39Z","title":"ParallelPC: an R package for efficient constraint based causal exploration"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1510.03042","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:bcbbf8bd3aecde3a29b46e5488be3d9702e1167260dd9f7c3a7e959f72a6931f","target":"record","created_at":"2026-05-18T01:30:32Z","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":"e274bd94a4f252b74a126a2c90e7c1293305be763b89eb026f0293665636b3bb","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2015-10-11T11:55:39Z","title_canon_sha256":"171215548cd85931e8ca6f038d48578874e1f159df5e60cf52d5a52cf674a55a"},"schema_version":"1.0","source":{"id":"1510.03042","kind":"arxiv","version":1}},"canonical_sha256":"5ed4f8122596cb76bf862cfb52b2f7567517e5bdf972f07dc727e704527e06e3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5ed4f8122596cb76bf862cfb52b2f7567517e5bdf972f07dc727e704527e06e3","first_computed_at":"2026-05-18T01:30:32.884448Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:30:32.884448Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/PZm+P0VvZ5tKIzYlriG20OFs6jNTMh9ltEUtkrkMNEL7Y+EqrlUvQl33q8k7lXYs57GN0GF7aAuocd33enZDQ==","signature_status":"signed_v1","signed_at":"2026-05-18T01:30:32.885010Z","signed_message":"canonical_sha256_bytes"},"source_id":"1510.03042","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bcbbf8bd3aecde3a29b46e5488be3d9702e1167260dd9f7c3a7e959f72a6931f","sha256:598dbff8fcc23d354398c91915414c0a6df81be0673fb593a963fd36178fc32a"],"state_sha256":"84f26c603b9d72340ddac8b497a585c9c5f8bbc56d1f2e04c4b97f4562fafdf5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UoIljVZ76qcOikzF6ygmpSFeMEaWHUnqkI8H2Tc7SjubGAQrGFKFhOx+T7mwvhvRLS89ZE3WbRCYMir5dUFGBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T13:11:11.820296Z","bundle_sha256":"7f1b433cc706ad803b6ea02ea72d122e0d7483e4d4b9ffdb8f135e4205231088"}}