{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:M23MTFQZEPFH5VWPKCCAJSP7X4","short_pith_number":"pith:M23MTFQZ","schema_version":"1.0","canonical_sha256":"66b6c9961923ca7ed6cf508404c9ffbf00209db444de9a8236b3faae412886eb","source":{"kind":"arxiv","id":"1303.1461","version":1},"attestation_state":"computed","paper":{"title":"Forecasting Sleep Apnea with Dynamic Network Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Adam Galper, Paul Dagum","submitted_at":"2013-03-06T14:19:03Z","abstract_excerpt":"Dynamic network models (DNMs) are belief networks for temporal reasoning.  The DNM methodology combines techniques from time series analysis and probabilistic reasoning to provide (1) a knowledge representation that integrates noncontemporaneous and contemporaneous dependencies and (2) methods for iteratively refining these dependencies in response to the effects of exogenous influences.  We use belief-network inference algorithms to perform forecasting, control, and discrete event simulation on DNMs.  The belief network formulation allows us to move beyond the traditional assumptions of linea"},"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":"1303.1461","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2013-03-06T14:19:03Z","cross_cats_sorted":[],"title_canon_sha256":"973607c6e7497f38aa43a5a75f96c5f60bbd1e5476ea7c4a232d3afeafb1f0a5","abstract_canon_sha256":"425916873f0bfbb5e68cf821296c597aa90e619d9f6a37e550f82b3e0ab4eff7"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:31:42.807304Z","signature_b64":"1FSq4FG/fG3BuQvgioahcU5u6cDyq6LiN9bK+vUJvGCCPwblVHv1Lco0+WTlPH9BRncUy4u0/RcrhGKN5ex1AA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"66b6c9961923ca7ed6cf508404c9ffbf00209db444de9a8236b3faae412886eb","last_reissued_at":"2026-05-18T03:31:42.806549Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:31:42.806549Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Forecasting Sleep Apnea with Dynamic Network Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Adam Galper, Paul Dagum","submitted_at":"2013-03-06T14:19:03Z","abstract_excerpt":"Dynamic network models (DNMs) are belief networks for temporal reasoning.  The DNM methodology combines techniques from time series analysis and probabilistic reasoning to provide (1) a knowledge representation that integrates noncontemporaneous and contemporaneous dependencies and (2) methods for iteratively refining these dependencies in response to the effects of exogenous influences.  We use belief-network inference algorithms to perform forecasting, control, and discrete event simulation on DNMs.  The belief network formulation allows us to move beyond the traditional assumptions of linea"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1303.1461","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":"1303.1461","created_at":"2026-05-18T03:31:42.806650+00:00"},{"alias_kind":"arxiv_version","alias_value":"1303.1461v1","created_at":"2026-05-18T03:31:42.806650+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1303.1461","created_at":"2026-05-18T03:31:42.806650+00:00"},{"alias_kind":"pith_short_12","alias_value":"M23MTFQZEPFH","created_at":"2026-05-18T12:27:51.066281+00:00"},{"alias_kind":"pith_short_16","alias_value":"M23MTFQZEPFH5VWP","created_at":"2026-05-18T12:27:51.066281+00:00"},{"alias_kind":"pith_short_8","alias_value":"M23MTFQZ","created_at":"2026-05-18T12:27:51.066281+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/M23MTFQZEPFH5VWPKCCAJSP7X4","json":"https://pith.science/pith/M23MTFQZEPFH5VWPKCCAJSP7X4.json","graph_json":"https://pith.science/api/pith-number/M23MTFQZEPFH5VWPKCCAJSP7X4/graph.json","events_json":"https://pith.science/api/pith-number/M23MTFQZEPFH5VWPKCCAJSP7X4/events.json","paper":"https://pith.science/paper/M23MTFQZ"},"agent_actions":{"view_html":"https://pith.science/pith/M23MTFQZEPFH5VWPKCCAJSP7X4","download_json":"https://pith.science/pith/M23MTFQZEPFH5VWPKCCAJSP7X4.json","view_paper":"https://pith.science/paper/M23MTFQZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1303.1461&json=true","fetch_graph":"https://pith.science/api/pith-number/M23MTFQZEPFH5VWPKCCAJSP7X4/graph.json","fetch_events":"https://pith.science/api/pith-number/M23MTFQZEPFH5VWPKCCAJSP7X4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/M23MTFQZEPFH5VWPKCCAJSP7X4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/M23MTFQZEPFH5VWPKCCAJSP7X4/action/storage_attestation","attest_author":"https://pith.science/pith/M23MTFQZEPFH5VWPKCCAJSP7X4/action/author_attestation","sign_citation":"https://pith.science/pith/M23MTFQZEPFH5VWPKCCAJSP7X4/action/citation_signature","submit_replication":"https://pith.science/pith/M23MTFQZEPFH5VWPKCCAJSP7X4/action/replication_record"}},"created_at":"2026-05-18T03:31:42.806650+00:00","updated_at":"2026-05-18T03:31:42.806650+00:00"}