{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:UCTLRBYCDV3IZ3MZ5YVH3BJ7HA","short_pith_number":"pith:UCTLRBYC","canonical_record":{"source":{"id":"2302.14230","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2023-02-28T01:28:18Z","cross_cats_sorted":["stat.AP"],"title_canon_sha256":"0349f991a7479484218468781d7757003dac4081d8086c948ad82c04c172f134","abstract_canon_sha256":"878bfb109258276f47044c02c4ba8b082ccc0c14c699dd62554a860934910811"},"schema_version":"1.0"},"canonical_sha256":"a0a6b887021d768ced99ee2a7d853f38038b3828d031131a72046a2e22c53031","source":{"kind":"arxiv","id":"2302.14230","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.14230","created_at":"2026-07-05T08:05:37Z"},{"alias_kind":"arxiv_version","alias_value":"2302.14230v2","created_at":"2026-07-05T08:05:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.14230","created_at":"2026-07-05T08:05:37Z"},{"alias_kind":"pith_short_12","alias_value":"UCTLRBYCDV3I","created_at":"2026-07-05T08:05:37Z"},{"alias_kind":"pith_short_16","alias_value":"UCTLRBYCDV3IZ3MZ","created_at":"2026-07-05T08:05:37Z"},{"alias_kind":"pith_short_8","alias_value":"UCTLRBYC","created_at":"2026-07-05T08:05:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:UCTLRBYCDV3IZ3MZ5YVH3BJ7HA","target":"record","payload":{"canonical_record":{"source":{"id":"2302.14230","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2023-02-28T01:28:18Z","cross_cats_sorted":["stat.AP"],"title_canon_sha256":"0349f991a7479484218468781d7757003dac4081d8086c948ad82c04c172f134","abstract_canon_sha256":"878bfb109258276f47044c02c4ba8b082ccc0c14c699dd62554a860934910811"},"schema_version":"1.0"},"canonical_sha256":"a0a6b887021d768ced99ee2a7d853f38038b3828d031131a72046a2e22c53031","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:05:37.338277Z","signature_b64":"Z4NSyKOrM7mMl1jNlKtruIPnN3N1JOudt3JeH1Vu+Fggp1rwNC5KkhmhfA2zdW+wPneYZu1T1yONZMFDSBPRCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a0a6b887021d768ced99ee2a7d853f38038b3828d031131a72046a2e22c53031","last_reissued_at":"2026-07-05T08:05:37.337833Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:05:37.337833Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2302.14230","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:05:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zjIILiVFKNEjnh//S3+ndEllIVx1cp6zAUbY9m5ybKWg4ZEwFoSlhGZVZlVik3n1wIU8s0JxbEynNNDUVKh1Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T13:55:42.141595Z"},"content_sha256":"84f8949476f314f22bd62b14fcaf83552170bdb0189245494cd2baf3092fff11","schema_version":"1.0","event_id":"sha256:84f8949476f314f22bd62b14fcaf83552170bdb0189245494cd2baf3092fff11"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:UCTLRBYCDV3IZ3MZ5YVH3BJ7HA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Optimal Priors for the Discounting Parameter of the Normalized Power Prior","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.AP"],"primary_cat":"stat.ME","authors_text":"Joseph G. Ibrahim, Luiz M. Carvalho, Matthew A. Psioda, Yueqi Shen","submitted_at":"2023-02-28T01:28:18Z","abstract_excerpt":"The power prior is a popular class of informative priors for incorporating information from historical data. It involves raising the likelihood for the historical data to a power, which acts as discounting parameter. When the discounting parameter is modelled as random, the normalized power prior is recommended. In this work, we prove that the marginal posterior for the discounting parameter for generalized linear models converges to a point mass at zero if there is any discrepancy between the historical and current data, and that it does not converge to a point mass at one when they are fully"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.14230","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2302.14230/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T08:05:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/b5fN4tBw1Obtd8qygC66R4ovaZl/wZEy+aDLtxS6ITkqwsj8CaRqCqN6u3AmKbOJARlABRWq/zNhVtgP9ufAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T13:55:42.141989Z"},"content_sha256":"bed1d8d8600a1f4d77b5cfeb3cb23c4153375227a65dc46f091d6fd53859c12d","schema_version":"1.0","event_id":"sha256:bed1d8d8600a1f4d77b5cfeb3cb23c4153375227a65dc46f091d6fd53859c12d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UCTLRBYCDV3IZ3MZ5YVH3BJ7HA/bundle.json","state_url":"https://pith.science/pith/UCTLRBYCDV3IZ3MZ5YVH3BJ7HA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UCTLRBYCDV3IZ3MZ5YVH3BJ7HA/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":"2026-07-08T13:55:42Z","links":{"resolver":"https://pith.science/pith/UCTLRBYCDV3IZ3MZ5YVH3BJ7HA","bundle":"https://pith.science/pith/UCTLRBYCDV3IZ3MZ5YVH3BJ7HA/bundle.json","state":"https://pith.science/pith/UCTLRBYCDV3IZ3MZ5YVH3BJ7HA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UCTLRBYCDV3IZ3MZ5YVH3BJ7HA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:UCTLRBYCDV3IZ3MZ5YVH3BJ7HA","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":"878bfb109258276f47044c02c4ba8b082ccc0c14c699dd62554a860934910811","cross_cats_sorted":["stat.AP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2023-02-28T01:28:18Z","title_canon_sha256":"0349f991a7479484218468781d7757003dac4081d8086c948ad82c04c172f134"},"schema_version":"1.0","source":{"id":"2302.14230","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.14230","created_at":"2026-07-05T08:05:37Z"},{"alias_kind":"arxiv_version","alias_value":"2302.14230v2","created_at":"2026-07-05T08:05:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.14230","created_at":"2026-07-05T08:05:37Z"},{"alias_kind":"pith_short_12","alias_value":"UCTLRBYCDV3I","created_at":"2026-07-05T08:05:37Z"},{"alias_kind":"pith_short_16","alias_value":"UCTLRBYCDV3IZ3MZ","created_at":"2026-07-05T08:05:37Z"},{"alias_kind":"pith_short_8","alias_value":"UCTLRBYC","created_at":"2026-07-05T08:05:37Z"}],"graph_snapshots":[{"event_id":"sha256:bed1d8d8600a1f4d77b5cfeb3cb23c4153375227a65dc46f091d6fd53859c12d","target":"graph","created_at":"2026-07-05T08:05:37Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2302.14230/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The power prior is a popular class of informative priors for incorporating information from historical data. It involves raising the likelihood for the historical data to a power, which acts as discounting parameter. When the discounting parameter is modelled as random, the normalized power prior is recommended. In this work, we prove that the marginal posterior for the discounting parameter for generalized linear models converges to a point mass at zero if there is any discrepancy between the historical and current data, and that it does not converge to a point mass at one when they are fully","authors_text":"Joseph G. Ibrahim, Luiz M. Carvalho, Matthew A. Psioda, Yueqi Shen","cross_cats":["stat.AP"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2023-02-28T01:28:18Z","title":"Optimal Priors for the Discounting Parameter of the Normalized Power Prior"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.14230","kind":"arxiv","version":2},"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":"sha256:84f8949476f314f22bd62b14fcaf83552170bdb0189245494cd2baf3092fff11","target":"record","created_at":"2026-07-05T08:05:37Z","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":"878bfb109258276f47044c02c4ba8b082ccc0c14c699dd62554a860934910811","cross_cats_sorted":["stat.AP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2023-02-28T01:28:18Z","title_canon_sha256":"0349f991a7479484218468781d7757003dac4081d8086c948ad82c04c172f134"},"schema_version":"1.0","source":{"id":"2302.14230","kind":"arxiv","version":2}},"canonical_sha256":"a0a6b887021d768ced99ee2a7d853f38038b3828d031131a72046a2e22c53031","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a0a6b887021d768ced99ee2a7d853f38038b3828d031131a72046a2e22c53031","first_computed_at":"2026-07-05T08:05:37.337833Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:05:37.337833Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Z4NSyKOrM7mMl1jNlKtruIPnN3N1JOudt3JeH1Vu+Fggp1rwNC5KkhmhfA2zdW+wPneYZu1T1yONZMFDSBPRCw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:05:37.338277Z","signed_message":"canonical_sha256_bytes"},"source_id":"2302.14230","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:84f8949476f314f22bd62b14fcaf83552170bdb0189245494cd2baf3092fff11","sha256:bed1d8d8600a1f4d77b5cfeb3cb23c4153375227a65dc46f091d6fd53859c12d"],"state_sha256":"5ca592b86cc8371efe837f008a070f7f4c3f9c89d1cf50dd4c1f0c164c322eba"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZkJ7WuEH1UrSmcNUDpV6oNqtWRbgjGZqusnZog5NOB/wS5nnc4g4RV5js1n/iaHziT5SnL4woWsFo9IjqP3WDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-08T13:55:42.144204Z","bundle_sha256":"0f02955ec58dc8fe755b87ba7e2f316119d5e9fdae1c1027ef560c81eb58d193"}}