{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:6BI75VPIJ6LMMKX3KTMIIZJPOF","short_pith_number":"pith:6BI75VPI","canonical_record":{"source":{"id":"1807.10981","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2018-07-28T22:41:20Z","cross_cats_sorted":[],"title_canon_sha256":"ceca9810f7f9ee7fd3133a971ef4ca701d6e78928d2e04248accb5fed6b81d6a","abstract_canon_sha256":"3b69e3817ddfd87488e337f5f2a5025d12a9a321240300752a020bba7e142731"},"schema_version":"1.0"},"canonical_sha256":"f051fed5e84f96c62afb54d884652f71797f9c1639a75526b1f3d1e770e4380a","source":{"kind":"arxiv","id":"1807.10981","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1807.10981","created_at":"2026-05-17T23:47:44Z"},{"alias_kind":"arxiv_version","alias_value":"1807.10981v3","created_at":"2026-05-17T23:47:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.10981","created_at":"2026-05-17T23:47:44Z"},{"alias_kind":"pith_short_12","alias_value":"6BI75VPIJ6LM","created_at":"2026-05-18T12:32:08Z"},{"alias_kind":"pith_short_16","alias_value":"6BI75VPIJ6LMMKX3","created_at":"2026-05-18T12:32:08Z"},{"alias_kind":"pith_short_8","alias_value":"6BI75VPI","created_at":"2026-05-18T12:32:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:6BI75VPIJ6LMMKX3KTMIIZJPOF","target":"record","payload":{"canonical_record":{"source":{"id":"1807.10981","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2018-07-28T22:41:20Z","cross_cats_sorted":[],"title_canon_sha256":"ceca9810f7f9ee7fd3133a971ef4ca701d6e78928d2e04248accb5fed6b81d6a","abstract_canon_sha256":"3b69e3817ddfd87488e337f5f2a5025d12a9a321240300752a020bba7e142731"},"schema_version":"1.0"},"canonical_sha256":"f051fed5e84f96c62afb54d884652f71797f9c1639a75526b1f3d1e770e4380a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:47:44.208955Z","signature_b64":"30eg3z5svB6TsrVMpYhalSUeKsCF6LwZkJfwwmW3Q658K+ho6XW5cigclJoTAS7k2K6o4An2/i1vnfmJXSAJBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f051fed5e84f96c62afb54d884652f71797f9c1639a75526b1f3d1e770e4380a","last_reissued_at":"2026-05-17T23:47:44.208329Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:47:44.208329Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1807.10981","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":"2026-05-17T23:47:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OzNp5yyBGKXtEv9fquO55/zx/abikEoti8Gu1vTUr6L8oJ+W7cKERehN4WQMJ1PHYl3cfLuvh9np6Tiza6kTCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T18:12:18.882133Z"},"content_sha256":"13c37cd681b8ba98b5e9f1a4bb908e60173c0872bd064b70678f1e316299dc31","schema_version":"1.0","event_id":"sha256:13c37cd681b8ba98b5e9f1a4bb908e60173c0872bd064b70678f1e316299dc31"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:6BI75VPIJ6LMMKX3KTMIIZJPOF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Making Recursive Bayesian Inference Accessible","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Brian M. Brost, Devin S. Johnson, Mevin B. Hooten","submitted_at":"2018-07-28T22:41:20Z","abstract_excerpt":"Bayesian models provide recursive inference naturally because they can formally reconcile new data and existing scientific information. However, popular use of Bayesian methods often avoids priors that are based on exact posterior distributions resulting from former studies. Two existing Recursive Bayesian methods are: Prior- and Proposal-Recursive Bayes. Prior-Recursive Bayes uses Bayesian updating, fitting models to partitions of data sequentially, and provides a way to accommodate new data as they become available using the posterior from the previous stage as the prior in the new stage bas"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.10981","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":"2026-05-17T23:47:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PfTqOM9ioqYK5YFHdXimigcjlczqNdONKQYC3tbzPP1dsd6HDrBpuvyFzC8Z3cyx+Ws8dd9VPsG5iA+TmlvrDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T18:12:18.882883Z"},"content_sha256":"9501316eaf7216e149296aaafb3837f202679e53839e4da291b34c212b5b4255","schema_version":"1.0","event_id":"sha256:9501316eaf7216e149296aaafb3837f202679e53839e4da291b34c212b5b4255"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6BI75VPIJ6LMMKX3KTMIIZJPOF/bundle.json","state_url":"https://pith.science/pith/6BI75VPIJ6LMMKX3KTMIIZJPOF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6BI75VPIJ6LMMKX3KTMIIZJPOF/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":"2026-05-31T18:12:18Z","links":{"resolver":"https://pith.science/pith/6BI75VPIJ6LMMKX3KTMIIZJPOF","bundle":"https://pith.science/pith/6BI75VPIJ6LMMKX3KTMIIZJPOF/bundle.json","state":"https://pith.science/pith/6BI75VPIJ6LMMKX3KTMIIZJPOF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6BI75VPIJ6LMMKX3KTMIIZJPOF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:6BI75VPIJ6LMMKX3KTMIIZJPOF","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":"3b69e3817ddfd87488e337f5f2a5025d12a9a321240300752a020bba7e142731","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2018-07-28T22:41:20Z","title_canon_sha256":"ceca9810f7f9ee7fd3133a971ef4ca701d6e78928d2e04248accb5fed6b81d6a"},"schema_version":"1.0","source":{"id":"1807.10981","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1807.10981","created_at":"2026-05-17T23:47:44Z"},{"alias_kind":"arxiv_version","alias_value":"1807.10981v3","created_at":"2026-05-17T23:47:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.10981","created_at":"2026-05-17T23:47:44Z"},{"alias_kind":"pith_short_12","alias_value":"6BI75VPIJ6LM","created_at":"2026-05-18T12:32:08Z"},{"alias_kind":"pith_short_16","alias_value":"6BI75VPIJ6LMMKX3","created_at":"2026-05-18T12:32:08Z"},{"alias_kind":"pith_short_8","alias_value":"6BI75VPI","created_at":"2026-05-18T12:32:08Z"}],"graph_snapshots":[{"event_id":"sha256:9501316eaf7216e149296aaafb3837f202679e53839e4da291b34c212b5b4255","target":"graph","created_at":"2026-05-17T23:47:44Z","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":"Bayesian models provide recursive inference naturally because they can formally reconcile new data and existing scientific information. However, popular use of Bayesian methods often avoids priors that are based on exact posterior distributions resulting from former studies. Two existing Recursive Bayesian methods are: Prior- and Proposal-Recursive Bayes. Prior-Recursive Bayes uses Bayesian updating, fitting models to partitions of data sequentially, and provides a way to accommodate new data as they become available using the posterior from the previous stage as the prior in the new stage bas","authors_text":"Brian M. Brost, Devin S. Johnson, Mevin B. Hooten","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2018-07-28T22:41:20Z","title":"Making Recursive Bayesian Inference Accessible"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.10981","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":"sha256:13c37cd681b8ba98b5e9f1a4bb908e60173c0872bd064b70678f1e316299dc31","target":"record","created_at":"2026-05-17T23:47:44Z","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":"3b69e3817ddfd87488e337f5f2a5025d12a9a321240300752a020bba7e142731","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2018-07-28T22:41:20Z","title_canon_sha256":"ceca9810f7f9ee7fd3133a971ef4ca701d6e78928d2e04248accb5fed6b81d6a"},"schema_version":"1.0","source":{"id":"1807.10981","kind":"arxiv","version":3}},"canonical_sha256":"f051fed5e84f96c62afb54d884652f71797f9c1639a75526b1f3d1e770e4380a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f051fed5e84f96c62afb54d884652f71797f9c1639a75526b1f3d1e770e4380a","first_computed_at":"2026-05-17T23:47:44.208329Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:47:44.208329Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"30eg3z5svB6TsrVMpYhalSUeKsCF6LwZkJfwwmW3Q658K+ho6XW5cigclJoTAS7k2K6o4An2/i1vnfmJXSAJBg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:47:44.208955Z","signed_message":"canonical_sha256_bytes"},"source_id":"1807.10981","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:13c37cd681b8ba98b5e9f1a4bb908e60173c0872bd064b70678f1e316299dc31","sha256:9501316eaf7216e149296aaafb3837f202679e53839e4da291b34c212b5b4255"],"state_sha256":"1ac601946f9b1afc99452b9e122ed025970418a0c9e0aec864d58eff9b2b25c5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IuBfRl4xrXURWOIwjafW5i/D63K1806fFjUFi5F17hjzfYpN6YwZ19TBt9DQAjqp0OHz6/31HpmZ8uFAXDC7Dg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T18:12:18.886779Z","bundle_sha256":"37bed63bba25d61a82951fcc0e8bb350b0ebc9fea7437308b0a588942bc5c8c6"}}