{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:3LS6ZWG4Y5QQW2CYI5SNW2ZFHB","short_pith_number":"pith:3LS6ZWG4","schema_version":"1.0","canonical_sha256":"dae5ecd8dcc7610b68584764db6b253862e0c03932866c3bd5bd215f09bd1fe4","source":{"kind":"arxiv","id":"2110.11896","version":1},"attestation_state":"computed","paper":{"title":"Multimodel Bayesian Analysis of Load Duration Effects in Lumber Reliability","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.AP","authors_text":"Martin Lysy, Samuel W.K. Wong, Yunfeng Yang","submitted_at":"2021-10-22T16:26:02Z","abstract_excerpt":"This paper evaluates the reliability of lumber, accounting for the duration-of-load (DOL) effect under different load profiles based on a multimodel Bayesian approach. Three individual DOL models previously used for reliability assessment are considered: the US model, the Canadian model, and the Gamma process model. Procedures for stochastic generation of residential, snow, and wind loads are also described. We propose Bayesian model-averaging (BMA) as a method for combining the reliability estimates of individual models under a given load profile that coherently accounts for statistical uncer"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2110.11896","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2021-10-22T16:26:02Z","cross_cats_sorted":[],"title_canon_sha256":"6d76760ebc12edb4cb44574b0e0576fa7785ca2bdd5e5f967e8bbc732e1bcfe1","abstract_canon_sha256":"e126d760e9ccf42c049855d46f24f5663060eabd862834c53b15fc5d38fd653d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:24:52.766866Z","signature_b64":"y7x7YF2dOUVWJG0YzIWUPTpCbrvPtyb7Gi2iASYa3nqPk1u+f+dr7BHrshsQEdNSFidzfXJ4eFZJxCnW2p5bAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dae5ecd8dcc7610b68584764db6b253862e0c03932866c3bd5bd215f09bd1fe4","last_reissued_at":"2026-07-05T03:24:52.766455Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:24:52.766455Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Multimodel Bayesian Analysis of Load Duration Effects in Lumber Reliability","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.AP","authors_text":"Martin Lysy, Samuel W.K. Wong, Yunfeng Yang","submitted_at":"2021-10-22T16:26:02Z","abstract_excerpt":"This paper evaluates the reliability of lumber, accounting for the duration-of-load (DOL) effect under different load profiles based on a multimodel Bayesian approach. Three individual DOL models previously used for reliability assessment are considered: the US model, the Canadian model, and the Gamma process model. Procedures for stochastic generation of residential, snow, and wind loads are also described. We propose Bayesian model-averaging (BMA) as a method for combining the reliability estimates of individual models under a given load profile that coherently accounts for statistical uncer"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.11896","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2110.11896/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2110.11896","created_at":"2026-07-05T03:24:52.766516+00:00"},{"alias_kind":"arxiv_version","alias_value":"2110.11896v1","created_at":"2026-07-05T03:24:52.766516+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.11896","created_at":"2026-07-05T03:24:52.766516+00:00"},{"alias_kind":"pith_short_12","alias_value":"3LS6ZWG4Y5QQ","created_at":"2026-07-05T03:24:52.766516+00:00"},{"alias_kind":"pith_short_16","alias_value":"3LS6ZWG4Y5QQW2CY","created_at":"2026-07-05T03:24:52.766516+00:00"},{"alias_kind":"pith_short_8","alias_value":"3LS6ZWG4","created_at":"2026-07-05T03:24:52.766516+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/3LS6ZWG4Y5QQW2CYI5SNW2ZFHB","json":"https://pith.science/pith/3LS6ZWG4Y5QQW2CYI5SNW2ZFHB.json","graph_json":"https://pith.science/api/pith-number/3LS6ZWG4Y5QQW2CYI5SNW2ZFHB/graph.json","events_json":"https://pith.science/api/pith-number/3LS6ZWG4Y5QQW2CYI5SNW2ZFHB/events.json","paper":"https://pith.science/paper/3LS6ZWG4"},"agent_actions":{"view_html":"https://pith.science/pith/3LS6ZWG4Y5QQW2CYI5SNW2ZFHB","download_json":"https://pith.science/pith/3LS6ZWG4Y5QQW2CYI5SNW2ZFHB.json","view_paper":"https://pith.science/paper/3LS6ZWG4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2110.11896&json=true","fetch_graph":"https://pith.science/api/pith-number/3LS6ZWG4Y5QQW2CYI5SNW2ZFHB/graph.json","fetch_events":"https://pith.science/api/pith-number/3LS6ZWG4Y5QQW2CYI5SNW2ZFHB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3LS6ZWG4Y5QQW2CYI5SNW2ZFHB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3LS6ZWG4Y5QQW2CYI5SNW2ZFHB/action/storage_attestation","attest_author":"https://pith.science/pith/3LS6ZWG4Y5QQW2CYI5SNW2ZFHB/action/author_attestation","sign_citation":"https://pith.science/pith/3LS6ZWG4Y5QQW2CYI5SNW2ZFHB/action/citation_signature","submit_replication":"https://pith.science/pith/3LS6ZWG4Y5QQW2CYI5SNW2ZFHB/action/replication_record"}},"created_at":"2026-07-05T03:24:52.766516+00:00","updated_at":"2026-07-05T03:24:52.766516+00:00"}