{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:CXUXLPRNUVMODHTCNSXQFK4GNQ","short_pith_number":"pith:CXUXLPRN","canonical_record":{"source":{"id":"1510.06989","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2015-10-23T16:52:52Z","cross_cats_sorted":[],"title_canon_sha256":"00a74a262b454abad1ef654d176c5ffa0d516c19f8cd42bd53ace5d369a4b607","abstract_canon_sha256":"b98e03359e4c07e9b085cef58458d70867fda9519f36b3fa3b9f57e9b26871f4"},"schema_version":"1.0"},"canonical_sha256":"15e975be2da558e19e626caf02ab866c181e782630d957339fc1a49aa687c6f8","source":{"kind":"arxiv","id":"1510.06989","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1510.06989","created_at":"2026-05-18T00:39:04Z"},{"alias_kind":"arxiv_version","alias_value":"1510.06989v3","created_at":"2026-05-18T00:39:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1510.06989","created_at":"2026-05-18T00:39:04Z"},{"alias_kind":"pith_short_12","alias_value":"CXUXLPRNUVMO","created_at":"2026-05-18T12:29:17Z"},{"alias_kind":"pith_short_16","alias_value":"CXUXLPRNUVMODHTC","created_at":"2026-05-18T12:29:17Z"},{"alias_kind":"pith_short_8","alias_value":"CXUXLPRN","created_at":"2026-05-18T12:29:17Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:CXUXLPRNUVMODHTCNSXQFK4GNQ","target":"record","payload":{"canonical_record":{"source":{"id":"1510.06989","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2015-10-23T16:52:52Z","cross_cats_sorted":[],"title_canon_sha256":"00a74a262b454abad1ef654d176c5ffa0d516c19f8cd42bd53ace5d369a4b607","abstract_canon_sha256":"b98e03359e4c07e9b085cef58458d70867fda9519f36b3fa3b9f57e9b26871f4"},"schema_version":"1.0"},"canonical_sha256":"15e975be2da558e19e626caf02ab866c181e782630d957339fc1a49aa687c6f8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:39:04.940676Z","signature_b64":"Uy0os7alLfzFEylDlGPDQbRShA1pqJoWDB+XfgpNWF9fFZN7zL2Y0mKSiBCsfBfrdlKoKwBVU8WI+V0ypLWOCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"15e975be2da558e19e626caf02ab866c181e782630d957339fc1a49aa687c6f8","last_reissued_at":"2026-05-18T00:39:04.940110Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:39:04.940110Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1510.06989","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":"2026-05-18T00:39:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"msWsHmuVdZe0+IPdmjuw6owhj7Lq/i8NQkcF7Bb3YRoqvnG4+ncjccUT2dikcEdCCjjrsgVBW9Ezh2OBRzWhAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T21:43:35.835466Z"},"content_sha256":"0c672aa084d805c1a17ab275a90e567f1e93c797176e5df29a27bcfc910a57fc","schema_version":"1.0","event_id":"sha256:0c672aa084d805c1a17ab275a90e567f1e93c797176e5df29a27bcfc910a57fc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:CXUXLPRNUVMODHTCNSXQFK4GNQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bayesian updating and model class selection with Subset Simulation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.CO","authors_text":"A. Garbuno-Inigo, F.A. DiazDelaO, I. Yoshida, S.K. Au","submitted_at":"2015-10-23T16:52:52Z","abstract_excerpt":"Identifying the parameters of a model and rating competitive models based on measured data has been among the most important but challenging topics in modern science and engineering, with great potential of application in structural system identification, updating and development of high fidelity models. These problems in principle can be tackled using a Bayesian probabilistic approach, where the parameters to be identified are treated as uncertain and their inference information are given in terms of their posterior (i.e., given data) probability distribution. For complex models encountered i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1510.06989","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":"2026-05-18T00:39:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"W3MAcXmoxqn2XA+afRWI8iZuNVPI926WLbkI7xcuVmchJncoqlXgYtJVuC47fTeL/Z04PCxD2040FC7fdwmwAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T21:43:35.836138Z"},"content_sha256":"549cc7d0a45e07150f6d22ddafd1da6f5d1d1f77d602e39fa6b60161d82bdc50","schema_version":"1.0","event_id":"sha256:549cc7d0a45e07150f6d22ddafd1da6f5d1d1f77d602e39fa6b60161d82bdc50"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CXUXLPRNUVMODHTCNSXQFK4GNQ/bundle.json","state_url":"https://pith.science/pith/CXUXLPRNUVMODHTCNSXQFK4GNQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CXUXLPRNUVMODHTCNSXQFK4GNQ/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":"2026-05-25T21:43:35Z","links":{"resolver":"https://pith.science/pith/CXUXLPRNUVMODHTCNSXQFK4GNQ","bundle":"https://pith.science/pith/CXUXLPRNUVMODHTCNSXQFK4GNQ/bundle.json","state":"https://pith.science/pith/CXUXLPRNUVMODHTCNSXQFK4GNQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CXUXLPRNUVMODHTCNSXQFK4GNQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:CXUXLPRNUVMODHTCNSXQFK4GNQ","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":"b98e03359e4c07e9b085cef58458d70867fda9519f36b3fa3b9f57e9b26871f4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2015-10-23T16:52:52Z","title_canon_sha256":"00a74a262b454abad1ef654d176c5ffa0d516c19f8cd42bd53ace5d369a4b607"},"schema_version":"1.0","source":{"id":"1510.06989","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1510.06989","created_at":"2026-05-18T00:39:04Z"},{"alias_kind":"arxiv_version","alias_value":"1510.06989v3","created_at":"2026-05-18T00:39:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1510.06989","created_at":"2026-05-18T00:39:04Z"},{"alias_kind":"pith_short_12","alias_value":"CXUXLPRNUVMO","created_at":"2026-05-18T12:29:17Z"},{"alias_kind":"pith_short_16","alias_value":"CXUXLPRNUVMODHTC","created_at":"2026-05-18T12:29:17Z"},{"alias_kind":"pith_short_8","alias_value":"CXUXLPRN","created_at":"2026-05-18T12:29:17Z"}],"graph_snapshots":[{"event_id":"sha256:549cc7d0a45e07150f6d22ddafd1da6f5d1d1f77d602e39fa6b60161d82bdc50","target":"graph","created_at":"2026-05-18T00:39:04Z","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":"Identifying the parameters of a model and rating competitive models based on measured data has been among the most important but challenging topics in modern science and engineering, with great potential of application in structural system identification, updating and development of high fidelity models. These problems in principle can be tackled using a Bayesian probabilistic approach, where the parameters to be identified are treated as uncertain and their inference information are given in terms of their posterior (i.e., given data) probability distribution. For complex models encountered i","authors_text":"A. Garbuno-Inigo, F.A. DiazDelaO, I. Yoshida, S.K. Au","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2015-10-23T16:52:52Z","title":"Bayesian updating and model class selection with Subset Simulation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1510.06989","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":"sha256:0c672aa084d805c1a17ab275a90e567f1e93c797176e5df29a27bcfc910a57fc","target":"record","created_at":"2026-05-18T00:39:04Z","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":"b98e03359e4c07e9b085cef58458d70867fda9519f36b3fa3b9f57e9b26871f4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2015-10-23T16:52:52Z","title_canon_sha256":"00a74a262b454abad1ef654d176c5ffa0d516c19f8cd42bd53ace5d369a4b607"},"schema_version":"1.0","source":{"id":"1510.06989","kind":"arxiv","version":3}},"canonical_sha256":"15e975be2da558e19e626caf02ab866c181e782630d957339fc1a49aa687c6f8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"15e975be2da558e19e626caf02ab866c181e782630d957339fc1a49aa687c6f8","first_computed_at":"2026-05-18T00:39:04.940110Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:39:04.940110Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Uy0os7alLfzFEylDlGPDQbRShA1pqJoWDB+XfgpNWF9fFZN7zL2Y0mKSiBCsfBfrdlKoKwBVU8WI+V0ypLWOCA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:39:04.940676Z","signed_message":"canonical_sha256_bytes"},"source_id":"1510.06989","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0c672aa084d805c1a17ab275a90e567f1e93c797176e5df29a27bcfc910a57fc","sha256:549cc7d0a45e07150f6d22ddafd1da6f5d1d1f77d602e39fa6b60161d82bdc50"],"state_sha256":"19fedcef3b64c6898845b280d8b4d7691b4d72ae76021259fb29b978042fdc6b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bAXg+YBYZUlpjmAT1LFam0bDijWTjxTGO18Fo17kZlGBIV6OPiywfndx8ljskgId9H+H5Hx0+T+XyiyF33iACg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T21:43:35.840292Z","bundle_sha256":"429ec33c6bbbec7a143c4679fa9ecffed71abf2afa46d851637c149938f78f65"}}