{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2011:EZU5YRAQLT4QY5BUMFYU3MG6UE","short_pith_number":"pith:EZU5YRAQ","canonical_record":{"source":{"id":"1108.2120","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2011-08-10T08:18:28Z","cross_cats_sorted":[],"title_canon_sha256":"5b6aa6d35b7239a9fb355a9b836315cfc5e1fae0939b29b5e1240d4e33038932","abstract_canon_sha256":"51d43bd58e286f0cd9f410e42a023819cc8bdaa1cb299e65340a66b5fa43742f"},"schema_version":"1.0"},"canonical_sha256":"2669dc44105cf90c743461714db0dea10b56bdcab75e0242d6f52fce05b27c65","source":{"kind":"arxiv","id":"1108.2120","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1108.2120","created_at":"2026-05-18T04:15:49Z"},{"alias_kind":"arxiv_version","alias_value":"1108.2120v1","created_at":"2026-05-18T04:15:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1108.2120","created_at":"2026-05-18T04:15:49Z"},{"alias_kind":"pith_short_12","alias_value":"EZU5YRAQLT4Q","created_at":"2026-05-18T12:26:28Z"},{"alias_kind":"pith_short_16","alias_value":"EZU5YRAQLT4QY5BU","created_at":"2026-05-18T12:26:28Z"},{"alias_kind":"pith_short_8","alias_value":"EZU5YRAQ","created_at":"2026-05-18T12:26:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2011:EZU5YRAQLT4QY5BUMFYU3MG6UE","target":"record","payload":{"canonical_record":{"source":{"id":"1108.2120","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2011-08-10T08:18:28Z","cross_cats_sorted":[],"title_canon_sha256":"5b6aa6d35b7239a9fb355a9b836315cfc5e1fae0939b29b5e1240d4e33038932","abstract_canon_sha256":"51d43bd58e286f0cd9f410e42a023819cc8bdaa1cb299e65340a66b5fa43742f"},"schema_version":"1.0"},"canonical_sha256":"2669dc44105cf90c743461714db0dea10b56bdcab75e0242d6f52fce05b27c65","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T04:15:49.320379Z","signature_b64":"4DBOwN0NYRaGZCpNyqsTvIVHw/1c6JC305qF5dWR8fOWV1hji/QYsOTaO9Xh+OaRZ4iEHLP8lEMPe08OWDgJDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2669dc44105cf90c743461714db0dea10b56bdcab75e0242d6f52fce05b27c65","last_reissued_at":"2026-05-18T04:15:49.319787Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T04:15:49.319787Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1108.2120","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":"2026-05-18T04:15:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nolJzyNHyl0lKyuukbY3yzz4EUajh/qt88D0o89GafyDMoT3Mtqj74j4Vuyo7z/NJOysfqzj2cYdHrTdT6LsAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T04:01:25.123354Z"},"content_sha256":"0969c894deb733f378964c9d38fa65a6d556dacc447618f9ecc2d3f45e6c656b","schema_version":"1.0","event_id":"sha256:0969c894deb733f378964c9d38fa65a6d556dacc447618f9ecc2d3f45e6c656b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2011:EZU5YRAQLT4QY5BUMFYU3MG6UE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Objective Priors: An Introduction for Frequentists","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Malay Ghosh","submitted_at":"2011-08-10T08:18:28Z","abstract_excerpt":"Bayesian methods are increasingly applied in these days in the theory and practice of statistics. Any Bayesian inference depends on a likelihood and a prior. Ideally one would like to elicit a prior from related sources of information or past data. However, in its absence, Bayesian methods need to rely on some \"objective\" or \"default\" priors, and the resulting posterior inference can still be quite valuable. Not surprisingly, over the years, the catalog of objective priors also has become prohibitively large, and one has to set some specific criteria for the selection of such priors. Our aim i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1108.2120","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":"2026-05-18T04:15:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"neEcpft2yvPN5nTfZElpfHYSMY8SpdvzTdSoqTV6s7j8S3u48EDNUYr1qIS8hOugkeQFb2+zRBVnn4rXfsxXCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T04:01:25.123709Z"},"content_sha256":"a5dca96ad9a528396b4d2378cfab01a23fc15f125e79bbd61e50923d62317040","schema_version":"1.0","event_id":"sha256:a5dca96ad9a528396b4d2378cfab01a23fc15f125e79bbd61e50923d62317040"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EZU5YRAQLT4QY5BUMFYU3MG6UE/bundle.json","state_url":"https://pith.science/pith/EZU5YRAQLT4QY5BUMFYU3MG6UE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EZU5YRAQLT4QY5BUMFYU3MG6UE/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":"2026-06-01T04:01:25Z","links":{"resolver":"https://pith.science/pith/EZU5YRAQLT4QY5BUMFYU3MG6UE","bundle":"https://pith.science/pith/EZU5YRAQLT4QY5BUMFYU3MG6UE/bundle.json","state":"https://pith.science/pith/EZU5YRAQLT4QY5BUMFYU3MG6UE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EZU5YRAQLT4QY5BUMFYU3MG6UE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2011:EZU5YRAQLT4QY5BUMFYU3MG6UE","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":"51d43bd58e286f0cd9f410e42a023819cc8bdaa1cb299e65340a66b5fa43742f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2011-08-10T08:18:28Z","title_canon_sha256":"5b6aa6d35b7239a9fb355a9b836315cfc5e1fae0939b29b5e1240d4e33038932"},"schema_version":"1.0","source":{"id":"1108.2120","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1108.2120","created_at":"2026-05-18T04:15:49Z"},{"alias_kind":"arxiv_version","alias_value":"1108.2120v1","created_at":"2026-05-18T04:15:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1108.2120","created_at":"2026-05-18T04:15:49Z"},{"alias_kind":"pith_short_12","alias_value":"EZU5YRAQLT4Q","created_at":"2026-05-18T12:26:28Z"},{"alias_kind":"pith_short_16","alias_value":"EZU5YRAQLT4QY5BU","created_at":"2026-05-18T12:26:28Z"},{"alias_kind":"pith_short_8","alias_value":"EZU5YRAQ","created_at":"2026-05-18T12:26:28Z"}],"graph_snapshots":[{"event_id":"sha256:a5dca96ad9a528396b4d2378cfab01a23fc15f125e79bbd61e50923d62317040","target":"graph","created_at":"2026-05-18T04:15:49Z","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 methods are increasingly applied in these days in the theory and practice of statistics. Any Bayesian inference depends on a likelihood and a prior. Ideally one would like to elicit a prior from related sources of information or past data. However, in its absence, Bayesian methods need to rely on some \"objective\" or \"default\" priors, and the resulting posterior inference can still be quite valuable. Not surprisingly, over the years, the catalog of objective priors also has become prohibitively large, and one has to set some specific criteria for the selection of such priors. Our aim i","authors_text":"Malay Ghosh","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2011-08-10T08:18:28Z","title":"Objective Priors: An Introduction for Frequentists"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1108.2120","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":"sha256:0969c894deb733f378964c9d38fa65a6d556dacc447618f9ecc2d3f45e6c656b","target":"record","created_at":"2026-05-18T04:15:49Z","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":"51d43bd58e286f0cd9f410e42a023819cc8bdaa1cb299e65340a66b5fa43742f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2011-08-10T08:18:28Z","title_canon_sha256":"5b6aa6d35b7239a9fb355a9b836315cfc5e1fae0939b29b5e1240d4e33038932"},"schema_version":"1.0","source":{"id":"1108.2120","kind":"arxiv","version":1}},"canonical_sha256":"2669dc44105cf90c743461714db0dea10b56bdcab75e0242d6f52fce05b27c65","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2669dc44105cf90c743461714db0dea10b56bdcab75e0242d6f52fce05b27c65","first_computed_at":"2026-05-18T04:15:49.319787Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T04:15:49.319787Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4DBOwN0NYRaGZCpNyqsTvIVHw/1c6JC305qF5dWR8fOWV1hji/QYsOTaO9Xh+OaRZ4iEHLP8lEMPe08OWDgJDw==","signature_status":"signed_v1","signed_at":"2026-05-18T04:15:49.320379Z","signed_message":"canonical_sha256_bytes"},"source_id":"1108.2120","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0969c894deb733f378964c9d38fa65a6d556dacc447618f9ecc2d3f45e6c656b","sha256:a5dca96ad9a528396b4d2378cfab01a23fc15f125e79bbd61e50923d62317040"],"state_sha256":"77de1609e9364c0b4d61a2d8f02a2b6bc1c411f62fd57ea5c21c2860bc0fdc37"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"liYR21DAuroX/rQLhNaXdSR5JUxOaNcmbPTEfZ9zPaE9okXluApMW1KmZhnugBgqEk+saOEdVyxM8Mi4blP3DQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T04:01:25.125894Z","bundle_sha256":"c1033716055a3ae043d90831f5b99facf4e06bc9d2fc1845cf5246587b14fe21"}}