{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:PMOOIUUNWZZPTP7AKMSH5N2PPF","short_pith_number":"pith:PMOOIUUN","schema_version":"1.0","canonical_sha256":"7b1ce4528db672f9bfe053247eb74f7945c0d7395372f6c52cbba7080dd0653f","source":{"kind":"arxiv","id":"2606.19560","version":1},"attestation_state":"computed","paper":{"title":"Understanding Key Features of Time Series Foundation Models from Epidemic Forecasting","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Alireza Jafari, Aniruddha Adiga, Geoffrey C. Fox, Judy Fox, Madhav Marathe","submitted_at":"2026-06-17T20:01:48Z","abstract_excerpt":"Seasonal influenza infects millions of people and causes substantial morbidity and mortality in the United States each year, making accurate short-term forecasting a core public-health need. Reliable forecasts of epidemic time series can inform vaccination timing, hospital staffing, and resource allocation, yet the comparative behavior of modern forecasting architectures on infectious-disease surveillance data remains insufficiently characterized. We address this gap through a systematic evaluation of regional influenza forecasting using influenza-like illness surveillance and influenza-associ"},"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":"2606.19560","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-17T20:01:48Z","cross_cats_sorted":[],"title_canon_sha256":"99824de046739a1ad76f3930c0d79537bb202c3c7bd739ceff18690377b76cbf","abstract_canon_sha256":"7f247b48cad35033c79b6116c316ae1872bea06039ae066a336b5edf6ac72da1"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-19T16:12:28.947273Z","signature_b64":"f5Otebveju3ri8ZmqyM4AXBFGTJhMFdw1XhqZ0vhl4bOweA4ivFy3L7AeZLKRk+9q8HrDeQzv9xo7rIpCtB5CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7b1ce4528db672f9bfe053247eb74f7945c0d7395372f6c52cbba7080dd0653f","last_reissued_at":"2026-06-19T16:12:28.946907Z","signature_status":"signed_v1","first_computed_at":"2026-06-19T16:12:28.946907Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Understanding Key Features of Time Series Foundation Models from Epidemic Forecasting","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Alireza Jafari, Aniruddha Adiga, Geoffrey C. Fox, Judy Fox, Madhav Marathe","submitted_at":"2026-06-17T20:01:48Z","abstract_excerpt":"Seasonal influenza infects millions of people and causes substantial morbidity and mortality in the United States each year, making accurate short-term forecasting a core public-health need. Reliable forecasts of epidemic time series can inform vaccination timing, hospital staffing, and resource allocation, yet the comparative behavior of modern forecasting architectures on infectious-disease surveillance data remains insufficiently characterized. We address this gap through a systematic evaluation of regional influenza forecasting using influenza-like illness surveillance and influenza-associ"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.19560","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/2606.19560/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":"2606.19560","created_at":"2026-06-19T16:12:28.946969+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.19560v1","created_at":"2026-06-19T16:12:28.946969+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.19560","created_at":"2026-06-19T16:12:28.946969+00:00"},{"alias_kind":"pith_short_12","alias_value":"PMOOIUUNWZZP","created_at":"2026-06-19T16:12:28.946969+00:00"},{"alias_kind":"pith_short_16","alias_value":"PMOOIUUNWZZPTP7A","created_at":"2026-06-19T16:12:28.946969+00:00"},{"alias_kind":"pith_short_8","alias_value":"PMOOIUUN","created_at":"2026-06-19T16:12:28.946969+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/PMOOIUUNWZZPTP7AKMSH5N2PPF","json":"https://pith.science/pith/PMOOIUUNWZZPTP7AKMSH5N2PPF.json","graph_json":"https://pith.science/api/pith-number/PMOOIUUNWZZPTP7AKMSH5N2PPF/graph.json","events_json":"https://pith.science/api/pith-number/PMOOIUUNWZZPTP7AKMSH5N2PPF/events.json","paper":"https://pith.science/paper/PMOOIUUN"},"agent_actions":{"view_html":"https://pith.science/pith/PMOOIUUNWZZPTP7AKMSH5N2PPF","download_json":"https://pith.science/pith/PMOOIUUNWZZPTP7AKMSH5N2PPF.json","view_paper":"https://pith.science/paper/PMOOIUUN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.19560&json=true","fetch_graph":"https://pith.science/api/pith-number/PMOOIUUNWZZPTP7AKMSH5N2PPF/graph.json","fetch_events":"https://pith.science/api/pith-number/PMOOIUUNWZZPTP7AKMSH5N2PPF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/PMOOIUUNWZZPTP7AKMSH5N2PPF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/PMOOIUUNWZZPTP7AKMSH5N2PPF/action/storage_attestation","attest_author":"https://pith.science/pith/PMOOIUUNWZZPTP7AKMSH5N2PPF/action/author_attestation","sign_citation":"https://pith.science/pith/PMOOIUUNWZZPTP7AKMSH5N2PPF/action/citation_signature","submit_replication":"https://pith.science/pith/PMOOIUUNWZZPTP7AKMSH5N2PPF/action/replication_record"}},"created_at":"2026-06-19T16:12:28.946969+00:00","updated_at":"2026-06-19T16:12:28.946969+00:00"}