{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:2UJSDECRQWKWQB75BDLIG5CVEI","short_pith_number":"pith:2UJSDECR","schema_version":"1.0","canonical_sha256":"d51321905185956807fd08d6837455223217b56188d5fa7edd5d8e2d18769b1c","source":{"kind":"arxiv","id":"1605.07924","version":1},"attestation_state":"computed","paper":{"title":"Modelling and Bayesian analysis of the Abakaliki Smallpox Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.CO"],"primary_cat":"stat.AP","authors_text":"Jessica E. Stockdale, Philip D. O'Neill, Theodore Kypraios","submitted_at":"2016-05-25T15:11:25Z","abstract_excerpt":"The celebrated Abakaliki smallpox data have appeared numerous times in the epidemic modelling literature, but in almost all cases only a specific subset of the data is considered. There is one previous analysis of the full data set, but this relies on approximation methods to derive a likelihood. The data themselves continue to be of interest due to concerns about the possible re-emergence of smallpox as a bioterrorism weapon. We present the first full Bayesian analysis using data-augmentation Markov chain Monte Carlo methods which avoid the need for likelihood approximations. Results include "},"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":"1605.07924","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2016-05-25T15:11:25Z","cross_cats_sorted":["stat.CO"],"title_canon_sha256":"0ca7d98c073e7071f80cb396aa8fb3e8623c4f21660928eea61e7918f68feb2f","abstract_canon_sha256":"59573642ac7dde06c5e5504d288c118f3bf361604621d2df0d960442d5cf9e11"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:13:38.771079Z","signature_b64":"z/mWRvfYS1pVoKknLvXSnX+FrNSH42Lxtomz5hMngdhmmmnkkUWgDhdhIU5GGTYTOz3UNchLBePZeOpgl+8xCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d51321905185956807fd08d6837455223217b56188d5fa7edd5d8e2d18769b1c","last_reissued_at":"2026-05-18T01:13:38.770448Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:13:38.770448Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Modelling and Bayesian analysis of the Abakaliki Smallpox Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.CO"],"primary_cat":"stat.AP","authors_text":"Jessica E. Stockdale, Philip D. O'Neill, Theodore Kypraios","submitted_at":"2016-05-25T15:11:25Z","abstract_excerpt":"The celebrated Abakaliki smallpox data have appeared numerous times in the epidemic modelling literature, but in almost all cases only a specific subset of the data is considered. There is one previous analysis of the full data set, but this relies on approximation methods to derive a likelihood. The data themselves continue to be of interest due to concerns about the possible re-emergence of smallpox as a bioterrorism weapon. We present the first full Bayesian analysis using data-augmentation Markov chain Monte Carlo methods which avoid the need for likelihood approximations. Results include "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1605.07924","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1605.07924","created_at":"2026-05-18T01:13:38.770548+00:00"},{"alias_kind":"arxiv_version","alias_value":"1605.07924v1","created_at":"2026-05-18T01:13:38.770548+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1605.07924","created_at":"2026-05-18T01:13:38.770548+00:00"},{"alias_kind":"pith_short_12","alias_value":"2UJSDECRQWKW","created_at":"2026-05-18T12:29:55.572404+00:00"},{"alias_kind":"pith_short_16","alias_value":"2UJSDECRQWKWQB75","created_at":"2026-05-18T12:29:55.572404+00:00"},{"alias_kind":"pith_short_8","alias_value":"2UJSDECR","created_at":"2026-05-18T12:29:55.572404+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/2UJSDECRQWKWQB75BDLIG5CVEI","json":"https://pith.science/pith/2UJSDECRQWKWQB75BDLIG5CVEI.json","graph_json":"https://pith.science/api/pith-number/2UJSDECRQWKWQB75BDLIG5CVEI/graph.json","events_json":"https://pith.science/api/pith-number/2UJSDECRQWKWQB75BDLIG5CVEI/events.json","paper":"https://pith.science/paper/2UJSDECR"},"agent_actions":{"view_html":"https://pith.science/pith/2UJSDECRQWKWQB75BDLIG5CVEI","download_json":"https://pith.science/pith/2UJSDECRQWKWQB75BDLIG5CVEI.json","view_paper":"https://pith.science/paper/2UJSDECR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1605.07924&json=true","fetch_graph":"https://pith.science/api/pith-number/2UJSDECRQWKWQB75BDLIG5CVEI/graph.json","fetch_events":"https://pith.science/api/pith-number/2UJSDECRQWKWQB75BDLIG5CVEI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2UJSDECRQWKWQB75BDLIG5CVEI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2UJSDECRQWKWQB75BDLIG5CVEI/action/storage_attestation","attest_author":"https://pith.science/pith/2UJSDECRQWKWQB75BDLIG5CVEI/action/author_attestation","sign_citation":"https://pith.science/pith/2UJSDECRQWKWQB75BDLIG5CVEI/action/citation_signature","submit_replication":"https://pith.science/pith/2UJSDECRQWKWQB75BDLIG5CVEI/action/replication_record"}},"created_at":"2026-05-18T01:13:38.770548+00:00","updated_at":"2026-05-18T01:13:38.770548+00:00"}