{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:TCDSNNOTLE3JNKTZJS27A5Y7PU","short_pith_number":"pith:TCDSNNOT","canonical_record":{"source":{"id":"1708.04221","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2017-08-14T17:37:41Z","cross_cats_sorted":["stat.AP"],"title_canon_sha256":"c484ac4c93f3f1e12c9e6fc198349c946c3156480d4dc2e7540d3d7db2c11e68","abstract_canon_sha256":"6786affdabb4bdaaf74908c85e35b82bb0a159c08bca03eaef92418c93ee9e28"},"schema_version":"1.0"},"canonical_sha256":"988726b5d3593696aa794cb5f0771f7d0412cda5c7fa694b829fcf0edc391d5f","source":{"kind":"arxiv","id":"1708.04221","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.04221","created_at":"2026-05-18T00:38:06Z"},{"alias_kind":"arxiv_version","alias_value":"1708.04221v1","created_at":"2026-05-18T00:38:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.04221","created_at":"2026-05-18T00:38:06Z"},{"alias_kind":"pith_short_12","alias_value":"TCDSNNOTLE3J","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_16","alias_value":"TCDSNNOTLE3JNKTZ","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_8","alias_value":"TCDSNNOT","created_at":"2026-05-18T12:31:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:TCDSNNOTLE3JNKTZJS27A5Y7PU","target":"record","payload":{"canonical_record":{"source":{"id":"1708.04221","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2017-08-14T17:37:41Z","cross_cats_sorted":["stat.AP"],"title_canon_sha256":"c484ac4c93f3f1e12c9e6fc198349c946c3156480d4dc2e7540d3d7db2c11e68","abstract_canon_sha256":"6786affdabb4bdaaf74908c85e35b82bb0a159c08bca03eaef92418c93ee9e28"},"schema_version":"1.0"},"canonical_sha256":"988726b5d3593696aa794cb5f0771f7d0412cda5c7fa694b829fcf0edc391d5f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:38:06.751958Z","signature_b64":"tnpoPzS6JZhSknlkNpo5k8QjEcZGeBZGzNAz+Cr8SDI1jtLV/dHVH5v+ANS32iKDWKCWXbAMzFEQeaG8N/e6AA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"988726b5d3593696aa794cb5f0771f7d0412cda5c7fa694b829fcf0edc391d5f","last_reissued_at":"2026-05-18T00:38:06.751381Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:38:06.751381Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1708.04221","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":"2026-05-18T00:38:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ep3NvpIGS3lBNOnqIunZSERcN04q8AzGa0izKdHNiO/1h9lNvJp72uO3KhOG8meyjIZ0ERfWIsk8/cLVud1mCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T05:21:05.583120Z"},"content_sha256":"7c0ee74f969615ebd6b0f5fe0b94cb7270823b91ba956521e9c9a399d2c1baad","schema_version":"1.0","event_id":"sha256:7c0ee74f969615ebd6b0f5fe0b94cb7270823b91ba956521e9c9a399d2c1baad"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:TCDSNNOTLE3JNKTZJS27A5Y7PU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Efficient sequential Monte Carlo algorithms for integrated population models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.AP"],"primary_cat":"stat.ME","authors_text":"Alexandros Beskos, Axel Finke, Petros Dellaportas, Ruth King","submitted_at":"2017-08-14T17:37:41Z","abstract_excerpt":"State-space models are commonly used to describe different forms of ecological data. We consider the case of count data with observation errors. For such data the system process is typically multi-dimensional consisting of coupled Markov processes, where each component corresponds to a different characterisation of the population, such as age group, gender or breeding status. The associated system process equations describe the biological mechanisms under which the system evolves over time. However, there is often limited information in the count data alone to sensibly estimate demographic par"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.04221","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":"2026-05-18T00:38:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aGjWfjBhpV8NA2nourMPFistF07336ejOR5vIMq5PnPqsX8Z/JBSDZ2vGzE5136Eo4g57lLlh3iKaPSiXXgVCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T05:21:05.583494Z"},"content_sha256":"8be1c8aea305f445250aec7f72add500b065983edaa28419a8b97dc9bfb2520a","schema_version":"1.0","event_id":"sha256:8be1c8aea305f445250aec7f72add500b065983edaa28419a8b97dc9bfb2520a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TCDSNNOTLE3JNKTZJS27A5Y7PU/bundle.json","state_url":"https://pith.science/pith/TCDSNNOTLE3JNKTZJS27A5Y7PU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TCDSNNOTLE3JNKTZJS27A5Y7PU/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":"2026-06-03T05:21:05Z","links":{"resolver":"https://pith.science/pith/TCDSNNOTLE3JNKTZJS27A5Y7PU","bundle":"https://pith.science/pith/TCDSNNOTLE3JNKTZJS27A5Y7PU/bundle.json","state":"https://pith.science/pith/TCDSNNOTLE3JNKTZJS27A5Y7PU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TCDSNNOTLE3JNKTZJS27A5Y7PU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:TCDSNNOTLE3JNKTZJS27A5Y7PU","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":"6786affdabb4bdaaf74908c85e35b82bb0a159c08bca03eaef92418c93ee9e28","cross_cats_sorted":["stat.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2017-08-14T17:37:41Z","title_canon_sha256":"c484ac4c93f3f1e12c9e6fc198349c946c3156480d4dc2e7540d3d7db2c11e68"},"schema_version":"1.0","source":{"id":"1708.04221","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.04221","created_at":"2026-05-18T00:38:06Z"},{"alias_kind":"arxiv_version","alias_value":"1708.04221v1","created_at":"2026-05-18T00:38:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.04221","created_at":"2026-05-18T00:38:06Z"},{"alias_kind":"pith_short_12","alias_value":"TCDSNNOTLE3J","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_16","alias_value":"TCDSNNOTLE3JNKTZ","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_8","alias_value":"TCDSNNOT","created_at":"2026-05-18T12:31:46Z"}],"graph_snapshots":[{"event_id":"sha256:8be1c8aea305f445250aec7f72add500b065983edaa28419a8b97dc9bfb2520a","target":"graph","created_at":"2026-05-18T00:38:06Z","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":"State-space models are commonly used to describe different forms of ecological data. We consider the case of count data with observation errors. For such data the system process is typically multi-dimensional consisting of coupled Markov processes, where each component corresponds to a different characterisation of the population, such as age group, gender or breeding status. The associated system process equations describe the biological mechanisms under which the system evolves over time. However, there is often limited information in the count data alone to sensibly estimate demographic par","authors_text":"Alexandros Beskos, Axel Finke, Petros Dellaportas, Ruth King","cross_cats":["stat.AP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2017-08-14T17:37:41Z","title":"Efficient sequential Monte Carlo algorithms for integrated population models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.04221","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":"sha256:7c0ee74f969615ebd6b0f5fe0b94cb7270823b91ba956521e9c9a399d2c1baad","target":"record","created_at":"2026-05-18T00:38:06Z","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":"6786affdabb4bdaaf74908c85e35b82bb0a159c08bca03eaef92418c93ee9e28","cross_cats_sorted":["stat.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2017-08-14T17:37:41Z","title_canon_sha256":"c484ac4c93f3f1e12c9e6fc198349c946c3156480d4dc2e7540d3d7db2c11e68"},"schema_version":"1.0","source":{"id":"1708.04221","kind":"arxiv","version":1}},"canonical_sha256":"988726b5d3593696aa794cb5f0771f7d0412cda5c7fa694b829fcf0edc391d5f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"988726b5d3593696aa794cb5f0771f7d0412cda5c7fa694b829fcf0edc391d5f","first_computed_at":"2026-05-18T00:38:06.751381Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:38:06.751381Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tnpoPzS6JZhSknlkNpo5k8QjEcZGeBZGzNAz+Cr8SDI1jtLV/dHVH5v+ANS32iKDWKCWXbAMzFEQeaG8N/e6AA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:38:06.751958Z","signed_message":"canonical_sha256_bytes"},"source_id":"1708.04221","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7c0ee74f969615ebd6b0f5fe0b94cb7270823b91ba956521e9c9a399d2c1baad","sha256:8be1c8aea305f445250aec7f72add500b065983edaa28419a8b97dc9bfb2520a"],"state_sha256":"b78819928a27058feaec026f7988931c77b9e37d02a99449dd33f5baefe02d4c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hd3bxtQABA0ouMJtsdSZtpoBuikEJoGAZKmr8aa8Ng/yu12wqctFqaDnf8T215JUSGL3C1iWExJzSDh0PfIPBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T05:21:05.585422Z","bundle_sha256":"418ab0e8994b53d7ee380318752e104a131b0aceb1c9ab13a933e0ba9b4cec9b"}}