{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2013:DNV7DALO34DLO3CSNGP3GU3S52","short_pith_number":"pith:DNV7DALO","canonical_record":{"source":{"id":"1301.2917","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2013-01-14T10:41:12Z","cross_cats_sorted":["stat.CO"],"title_canon_sha256":"749ab040e81f62b835f55e78c520fa93d0de1a4d2b9378de2dbd576019704db9","abstract_canon_sha256":"afe2b52769ba97508a20659a2b8f55e0a229623d413b7ba899e1ce7609b833dc"},"schema_version":"1.0"},"canonical_sha256":"1b6bf1816edf06b76c52699fb35372ee9e532b8c87446b2753177c4a61acdfdc","source":{"kind":"arxiv","id":"1301.2917","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1301.2917","created_at":"2026-05-18T02:55:19Z"},{"alias_kind":"arxiv_version","alias_value":"1301.2917v3","created_at":"2026-05-18T02:55:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1301.2917","created_at":"2026-05-18T02:55:19Z"},{"alias_kind":"pith_short_12","alias_value":"DNV7DALO34DL","created_at":"2026-05-18T12:27:43Z"},{"alias_kind":"pith_short_16","alias_value":"DNV7DALO34DLO3CS","created_at":"2026-05-18T12:27:43Z"},{"alias_kind":"pith_short_8","alias_value":"DNV7DALO","created_at":"2026-05-18T12:27:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2013:DNV7DALO34DLO3CSNGP3GU3S52","target":"record","payload":{"canonical_record":{"source":{"id":"1301.2917","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2013-01-14T10:41:12Z","cross_cats_sorted":["stat.CO"],"title_canon_sha256":"749ab040e81f62b835f55e78c520fa93d0de1a4d2b9378de2dbd576019704db9","abstract_canon_sha256":"afe2b52769ba97508a20659a2b8f55e0a229623d413b7ba899e1ce7609b833dc"},"schema_version":"1.0"},"canonical_sha256":"1b6bf1816edf06b76c52699fb35372ee9e532b8c87446b2753177c4a61acdfdc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:55:19.415629Z","signature_b64":"5iwdWR2bL+Nj2QuzLV8ar1g6IP8xFUn140HyjyFVtGTo3pvZGfbEm1fE/QI1LkCdi6Xk5Wrjc3C3sWtlw1+1Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1b6bf1816edf06b76c52699fb35372ee9e532b8c87446b2753177c4a61acdfdc","last_reissued_at":"2026-05-18T02:55:19.415152Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:55:19.415152Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1301.2917","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T02:55:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"My9JB1/2mY6u9Y4AxLcYTJSuffnKWYZi6EAAS4wNyyX/zz5UH4kO73tCs7lK7tAsLiwHE6eDSxZc1M28/ZXjCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-29T18:39:31.575993Z"},"content_sha256":"558eb7276ebeab6be9c5c854c13da42f3cf7fa30c482aa90a75652e487c9222b","schema_version":"1.0","event_id":"sha256:558eb7276ebeab6be9c5c854c13da42f3cf7fa30c482aa90a75652e487c9222b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2013:DNV7DALO34DLO3CSNGP3GU3S52","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Evidence and Bayes factor estimation for Gibbs random fields","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.CO"],"primary_cat":"stat.ME","authors_text":"Nial Friel","submitted_at":"2013-01-14T10:41:12Z","abstract_excerpt":"Gibbs random fields play an important role in statistics. However they are complicated to work with due to an intractability of the likelihood function and there has been much work devoted to finding computational algorithms to allow Bayesian inference to be conducted for such so-called doubly intractable distributions. This paper extends this work and addresses the issue of estimating the evidence and Bayes factor for such models. The approach which we develop is shown to yield good performance."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1301.2917","kind":"arxiv","version":3},"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":"2026-05-18T02:55:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"K2fcCDM9GaiZZys1fVNfgKjb2spPqAZwvSvlHnlOWqWzf73wSfMjP1wgy2ChPLw4REEsnWPAQtGMUR3I9ofMDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-29T18:39:31.576365Z"},"content_sha256":"d4517b7e04e07236c185c19f5cefadad1f7d01a05185f2f7e139ca46c8a2d90f","schema_version":"1.0","event_id":"sha256:d4517b7e04e07236c185c19f5cefadad1f7d01a05185f2f7e139ca46c8a2d90f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DNV7DALO34DLO3CSNGP3GU3S52/bundle.json","state_url":"https://pith.science/pith/DNV7DALO34DLO3CSNGP3GU3S52/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DNV7DALO34DLO3CSNGP3GU3S52/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":"2026-06-29T18:39:31Z","links":{"resolver":"https://pith.science/pith/DNV7DALO34DLO3CSNGP3GU3S52","bundle":"https://pith.science/pith/DNV7DALO34DLO3CSNGP3GU3S52/bundle.json","state":"https://pith.science/pith/DNV7DALO34DLO3CSNGP3GU3S52/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DNV7DALO34DLO3CSNGP3GU3S52/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2013:DNV7DALO34DLO3CSNGP3GU3S52","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":"afe2b52769ba97508a20659a2b8f55e0a229623d413b7ba899e1ce7609b833dc","cross_cats_sorted":["stat.CO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2013-01-14T10:41:12Z","title_canon_sha256":"749ab040e81f62b835f55e78c520fa93d0de1a4d2b9378de2dbd576019704db9"},"schema_version":"1.0","source":{"id":"1301.2917","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1301.2917","created_at":"2026-05-18T02:55:19Z"},{"alias_kind":"arxiv_version","alias_value":"1301.2917v3","created_at":"2026-05-18T02:55:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1301.2917","created_at":"2026-05-18T02:55:19Z"},{"alias_kind":"pith_short_12","alias_value":"DNV7DALO34DL","created_at":"2026-05-18T12:27:43Z"},{"alias_kind":"pith_short_16","alias_value":"DNV7DALO34DLO3CS","created_at":"2026-05-18T12:27:43Z"},{"alias_kind":"pith_short_8","alias_value":"DNV7DALO","created_at":"2026-05-18T12:27:43Z"}],"graph_snapshots":[{"event_id":"sha256:d4517b7e04e07236c185c19f5cefadad1f7d01a05185f2f7e139ca46c8a2d90f","target":"graph","created_at":"2026-05-18T02:55:19Z","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":"Gibbs random fields play an important role in statistics. However they are complicated to work with due to an intractability of the likelihood function and there has been much work devoted to finding computational algorithms to allow Bayesian inference to be conducted for such so-called doubly intractable distributions. This paper extends this work and addresses the issue of estimating the evidence and Bayes factor for such models. The approach which we develop is shown to yield good performance.","authors_text":"Nial Friel","cross_cats":["stat.CO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2013-01-14T10:41:12Z","title":"Evidence and Bayes factor estimation for Gibbs random fields"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1301.2917","kind":"arxiv","version":3},"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":"sha256:558eb7276ebeab6be9c5c854c13da42f3cf7fa30c482aa90a75652e487c9222b","target":"record","created_at":"2026-05-18T02:55:19Z","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":"afe2b52769ba97508a20659a2b8f55e0a229623d413b7ba899e1ce7609b833dc","cross_cats_sorted":["stat.CO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2013-01-14T10:41:12Z","title_canon_sha256":"749ab040e81f62b835f55e78c520fa93d0de1a4d2b9378de2dbd576019704db9"},"schema_version":"1.0","source":{"id":"1301.2917","kind":"arxiv","version":3}},"canonical_sha256":"1b6bf1816edf06b76c52699fb35372ee9e532b8c87446b2753177c4a61acdfdc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1b6bf1816edf06b76c52699fb35372ee9e532b8c87446b2753177c4a61acdfdc","first_computed_at":"2026-05-18T02:55:19.415152Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:55:19.415152Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5iwdWR2bL+Nj2QuzLV8ar1g6IP8xFUn140HyjyFVtGTo3pvZGfbEm1fE/QI1LkCdi6Xk5Wrjc3C3sWtlw1+1Dg==","signature_status":"signed_v1","signed_at":"2026-05-18T02:55:19.415629Z","signed_message":"canonical_sha256_bytes"},"source_id":"1301.2917","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:558eb7276ebeab6be9c5c854c13da42f3cf7fa30c482aa90a75652e487c9222b","sha256:d4517b7e04e07236c185c19f5cefadad1f7d01a05185f2f7e139ca46c8a2d90f"],"state_sha256":"3f594eaf7cdf373cee2b518d3a62d439eda186c84d9ac386ade9ed66d914574d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AhOXIheQVa23zbgbKUoPvOJN0F0dnrTHgiquTa8qG8+wxQHhUQDMpZOHVDSiUMV2Hu7dUf/1POrgub1D8YZDBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-29T18:39:31.578334Z","bundle_sha256":"d176b0ec45de525d4e214ad9599f540b48fcb15d2cd561546945c213732ddb25"}}