{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:FSEXOERQ74KIBPYO4G7I2M5T33","short_pith_number":"pith:FSEXOERQ","schema_version":"1.0","canonical_sha256":"2c89771230ff1480bf0ee1be8d33b3dedbbade001544af5d4e268130f4fb77d6","source":{"kind":"arxiv","id":"2607.06916","version":1},"attestation_state":"computed","paper":{"title":"A Hierarchical Multilevel Inference Framework for Structural Cardiovascular Risk Modeling: County-Scale Analysis of Cardiovascular Mortality in Ohio and Pennsylvania (1999-2020)","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.AP","authors_text":"Christopher Blaszczak-Boxe, Jose Perez-Chavez, King-Fai Li, Mohammad Russel, Sium Gebremeriam, Yuk L. Yung","submitted_at":"2026-07-08T02:13:39Z","abstract_excerpt":"Cardiovascular mortality is shaped by interacting demographic, environmental, and structural processes operating across multiple spatial scales. Conventional epidemiologic analyses often rely on aggregate summaries or single-model formulations that obscure hierarchical variation and contextual heterogeneity. We present a reproducible multilevel statistical inference framework integrating Normal (age-adjusted), Poisson (count-based), and population-offset Poisson models to quantify cardiovascular mortality across nested geographic units while separating demographic effects from structural varia"},"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":"2607.06916","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2026-07-08T02:13:39Z","cross_cats_sorted":[],"title_canon_sha256":"6e1ca7e36897e9c44a2da4326ec034b4c9986f6b0d4c7f98ef5eeda04bfb2076","abstract_canon_sha256":"cda3dd7c5f7535b76b20e5bbc61d9aa97377d7ff7b1b3f92be69f36332bc87fc"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-09T00:19:39.785709Z","signature_b64":"SG5viLoslYQ8O7ID0kXuLBUjl2TRoXvgED1OYbL75arNx+bkudyE8caRj2HPB4/m53pOURXZJCCJ1je0VCj3BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2c89771230ff1480bf0ee1be8d33b3dedbbade001544af5d4e268130f4fb77d6","last_reissued_at":"2026-07-09T00:19:39.785263Z","signature_status":"signed_v1","first_computed_at":"2026-07-09T00:19:39.785263Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Hierarchical Multilevel Inference Framework for Structural Cardiovascular Risk Modeling: County-Scale Analysis of Cardiovascular Mortality in Ohio and Pennsylvania (1999-2020)","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.AP","authors_text":"Christopher Blaszczak-Boxe, Jose Perez-Chavez, King-Fai Li, Mohammad Russel, Sium Gebremeriam, Yuk L. Yung","submitted_at":"2026-07-08T02:13:39Z","abstract_excerpt":"Cardiovascular mortality is shaped by interacting demographic, environmental, and structural processes operating across multiple spatial scales. Conventional epidemiologic analyses often rely on aggregate summaries or single-model formulations that obscure hierarchical variation and contextual heterogeneity. We present a reproducible multilevel statistical inference framework integrating Normal (age-adjusted), Poisson (count-based), and population-offset Poisson models to quantify cardiovascular mortality across nested geographic units while separating demographic effects from structural varia"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.06916","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/2607.06916/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":"2607.06916","created_at":"2026-07-09T00:19:39.785335+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.06916v1","created_at":"2026-07-09T00:19:39.785335+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.06916","created_at":"2026-07-09T00:19:39.785335+00:00"},{"alias_kind":"pith_short_12","alias_value":"FSEXOERQ74KI","created_at":"2026-07-09T00:19:39.785335+00:00"},{"alias_kind":"pith_short_16","alias_value":"FSEXOERQ74KIBPYO","created_at":"2026-07-09T00:19:39.785335+00:00"},{"alias_kind":"pith_short_8","alias_value":"FSEXOERQ","created_at":"2026-07-09T00:19:39.785335+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/FSEXOERQ74KIBPYO4G7I2M5T33","json":"https://pith.science/pith/FSEXOERQ74KIBPYO4G7I2M5T33.json","graph_json":"https://pith.science/api/pith-number/FSEXOERQ74KIBPYO4G7I2M5T33/graph.json","events_json":"https://pith.science/api/pith-number/FSEXOERQ74KIBPYO4G7I2M5T33/events.json","paper":"https://pith.science/paper/FSEXOERQ"},"agent_actions":{"view_html":"https://pith.science/pith/FSEXOERQ74KIBPYO4G7I2M5T33","download_json":"https://pith.science/pith/FSEXOERQ74KIBPYO4G7I2M5T33.json","view_paper":"https://pith.science/paper/FSEXOERQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.06916&json=true","fetch_graph":"https://pith.science/api/pith-number/FSEXOERQ74KIBPYO4G7I2M5T33/graph.json","fetch_events":"https://pith.science/api/pith-number/FSEXOERQ74KIBPYO4G7I2M5T33/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/FSEXOERQ74KIBPYO4G7I2M5T33/action/timestamp_anchor","attest_storage":"https://pith.science/pith/FSEXOERQ74KIBPYO4G7I2M5T33/action/storage_attestation","attest_author":"https://pith.science/pith/FSEXOERQ74KIBPYO4G7I2M5T33/action/author_attestation","sign_citation":"https://pith.science/pith/FSEXOERQ74KIBPYO4G7I2M5T33/action/citation_signature","submit_replication":"https://pith.science/pith/FSEXOERQ74KIBPYO4G7I2M5T33/action/replication_record"}},"created_at":"2026-07-09T00:19:39.785335+00:00","updated_at":"2026-07-09T00:19:39.785335+00:00"}