{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2012:RIJYDFC2GUMTMOIVYKS5HEVUFL","short_pith_number":"pith:RIJYDFC2","canonical_record":{"source":{"id":"1209.3198","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2012-09-14T14:00:51Z","cross_cats_sorted":[],"title_canon_sha256":"41e89661cb2c42baaa407b431be51f78272d71755513ff9f30ba8a1656609872","abstract_canon_sha256":"b1e49db4f0d0cadf4f597d42d31b7ce38b906b08047c8773fcee489cb2d6a1ae"},"schema_version":"1.0"},"canonical_sha256":"8a1381945a3519363915c2a5d392b42ae081054eacdcc3c00c34249f1c83acaf","source":{"kind":"arxiv","id":"1209.3198","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1209.3198","created_at":"2026-05-18T03:21:08Z"},{"alias_kind":"arxiv_version","alias_value":"1209.3198v3","created_at":"2026-05-18T03:21:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1209.3198","created_at":"2026-05-18T03:21:08Z"},{"alias_kind":"pith_short_12","alias_value":"RIJYDFC2GUMT","created_at":"2026-05-18T12:27:20Z"},{"alias_kind":"pith_short_16","alias_value":"RIJYDFC2GUMTMOIV","created_at":"2026-05-18T12:27:20Z"},{"alias_kind":"pith_short_8","alias_value":"RIJYDFC2","created_at":"2026-05-18T12:27:20Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2012:RIJYDFC2GUMTMOIVYKS5HEVUFL","target":"record","payload":{"canonical_record":{"source":{"id":"1209.3198","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2012-09-14T14:00:51Z","cross_cats_sorted":[],"title_canon_sha256":"41e89661cb2c42baaa407b431be51f78272d71755513ff9f30ba8a1656609872","abstract_canon_sha256":"b1e49db4f0d0cadf4f597d42d31b7ce38b906b08047c8773fcee489cb2d6a1ae"},"schema_version":"1.0"},"canonical_sha256":"8a1381945a3519363915c2a5d392b42ae081054eacdcc3c00c34249f1c83acaf","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:21:08.478191Z","signature_b64":"eiXMtrz1pThiVPIhX08BgJTCd5Xr1C9bx2+YSx0fy5ZD38OPKrmI6SEgRyPGv3yWxWVhejGwqGFTOl7EvDQWDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8a1381945a3519363915c2a5d392b42ae081054eacdcc3c00c34249f1c83acaf","last_reissued_at":"2026-05-18T03:21:08.477643Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:21:08.477643Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1209.3198","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":"2026-05-18T03:21:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fjorv2C52qIsyx0kzoaATOimWBUvvvFaRL/yjG9IAmQAmpgTcciwYmC3V4AlNDx4+zWkPVcDlnJd4MmBTBolDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-21T23:51:18.527349Z"},"content_sha256":"c691a03d052a2133c79bcead1ba4f02214b40863fa77a40e850dc8e17174044d","schema_version":"1.0","event_id":"sha256:c691a03d052a2133c79bcead1ba4f02214b40863fa77a40e850dc8e17174044d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2012:RIJYDFC2GUMTMOIVYKS5HEVUFL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Improving power posterior estimation of statistical evidence","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.CO","authors_text":"Jason Wyse, Merrilee Hurn, Nial Friel","submitted_at":"2012-09-14T14:00:51Z","abstract_excerpt":"The statistical evidence (or marginal likelihood) is a key quantity in Bayesian statistics, allowing one to assess the probability of the data given the model under investigation. This paper focuses on refining the power posterior approach to improve estimation of the evidence. The power posterior method involves transitioning from the prior to the posterior by powering the likelihood by an inverse temperature. In common with other tempering algorithms, the power posterior involves some degree of tuning. The main contributions of this article are twofold -- we present a result from the numeric"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1209.3198","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":"2026-05-18T03:21:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tkiEc3V2NkmuJxyVaE4ProMG8jx+3MzAti0IUTRLlW+uyv1NUok9DJAZ2M6hHZe7vPvsSsbJ/UStrydfyUD9AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-21T23:51:18.527702Z"},"content_sha256":"d5e7bba545aa0e15e5f82bb6d705b915e2c1f25be10b4e2248126787c12eb72f","schema_version":"1.0","event_id":"sha256:d5e7bba545aa0e15e5f82bb6d705b915e2c1f25be10b4e2248126787c12eb72f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RIJYDFC2GUMTMOIVYKS5HEVUFL/bundle.json","state_url":"https://pith.science/pith/RIJYDFC2GUMTMOIVYKS5HEVUFL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RIJYDFC2GUMTMOIVYKS5HEVUFL/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":"2026-06-21T23:51:18Z","links":{"resolver":"https://pith.science/pith/RIJYDFC2GUMTMOIVYKS5HEVUFL","bundle":"https://pith.science/pith/RIJYDFC2GUMTMOIVYKS5HEVUFL/bundle.json","state":"https://pith.science/pith/RIJYDFC2GUMTMOIVYKS5HEVUFL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RIJYDFC2GUMTMOIVYKS5HEVUFL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2012:RIJYDFC2GUMTMOIVYKS5HEVUFL","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":"b1e49db4f0d0cadf4f597d42d31b7ce38b906b08047c8773fcee489cb2d6a1ae","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2012-09-14T14:00:51Z","title_canon_sha256":"41e89661cb2c42baaa407b431be51f78272d71755513ff9f30ba8a1656609872"},"schema_version":"1.0","source":{"id":"1209.3198","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1209.3198","created_at":"2026-05-18T03:21:08Z"},{"alias_kind":"arxiv_version","alias_value":"1209.3198v3","created_at":"2026-05-18T03:21:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1209.3198","created_at":"2026-05-18T03:21:08Z"},{"alias_kind":"pith_short_12","alias_value":"RIJYDFC2GUMT","created_at":"2026-05-18T12:27:20Z"},{"alias_kind":"pith_short_16","alias_value":"RIJYDFC2GUMTMOIV","created_at":"2026-05-18T12:27:20Z"},{"alias_kind":"pith_short_8","alias_value":"RIJYDFC2","created_at":"2026-05-18T12:27:20Z"}],"graph_snapshots":[{"event_id":"sha256:d5e7bba545aa0e15e5f82bb6d705b915e2c1f25be10b4e2248126787c12eb72f","target":"graph","created_at":"2026-05-18T03:21:08Z","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":"The statistical evidence (or marginal likelihood) is a key quantity in Bayesian statistics, allowing one to assess the probability of the data given the model under investigation. This paper focuses on refining the power posterior approach to improve estimation of the evidence. The power posterior method involves transitioning from the prior to the posterior by powering the likelihood by an inverse temperature. In common with other tempering algorithms, the power posterior involves some degree of tuning. The main contributions of this article are twofold -- we present a result from the numeric","authors_text":"Jason Wyse, Merrilee Hurn, Nial Friel","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2012-09-14T14:00:51Z","title":"Improving power posterior estimation of statistical evidence"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1209.3198","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:c691a03d052a2133c79bcead1ba4f02214b40863fa77a40e850dc8e17174044d","target":"record","created_at":"2026-05-18T03:21:08Z","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":"b1e49db4f0d0cadf4f597d42d31b7ce38b906b08047c8773fcee489cb2d6a1ae","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2012-09-14T14:00:51Z","title_canon_sha256":"41e89661cb2c42baaa407b431be51f78272d71755513ff9f30ba8a1656609872"},"schema_version":"1.0","source":{"id":"1209.3198","kind":"arxiv","version":3}},"canonical_sha256":"8a1381945a3519363915c2a5d392b42ae081054eacdcc3c00c34249f1c83acaf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8a1381945a3519363915c2a5d392b42ae081054eacdcc3c00c34249f1c83acaf","first_computed_at":"2026-05-18T03:21:08.477643Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:21:08.477643Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"eiXMtrz1pThiVPIhX08BgJTCd5Xr1C9bx2+YSx0fy5ZD38OPKrmI6SEgRyPGv3yWxWVhejGwqGFTOl7EvDQWDw==","signature_status":"signed_v1","signed_at":"2026-05-18T03:21:08.478191Z","signed_message":"canonical_sha256_bytes"},"source_id":"1209.3198","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c691a03d052a2133c79bcead1ba4f02214b40863fa77a40e850dc8e17174044d","sha256:d5e7bba545aa0e15e5f82bb6d705b915e2c1f25be10b4e2248126787c12eb72f"],"state_sha256":"2e474ff361c645c3bf4c04f0d06af5611d96d15fbb1e40725da3c8a604b4fe1e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8lb6n0LgYAXzRi4z55PYFcjqtgasFb0RDoAu01QYj7/keN4jVnSL29YT1NlUmKM7k+EEhHbBdgcmsL6R4KA2AA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-21T23:51:18.529677Z","bundle_sha256":"da496dd5d818d8c597f8fbb8f7dfa133c1d1ff1f2eebaf5a96f84b69b29d5727"}}