{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:N5M52EMXBKQIVBUMMHAZTPU7HI","short_pith_number":"pith:N5M52EMX","schema_version":"1.0","canonical_sha256":"6f59dd11970aa08a868c61c199be9f3a1d709c4cf11d2ee1194b86a65504fbca","source":{"kind":"arxiv","id":"2106.04420","version":8},"attestation_state":"computed","paper":{"title":"Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CY"],"primary_cat":"cs.LG","authors_text":"Alexander Rodr\\'iguez, B. Aditya Prakash, Harshavardhan Kamarthi","submitted_at":"2021-06-08T14:48:20Z","abstract_excerpt":"In real-time forecasting in public health, data collection is a non-trivial and demanding task. Often after initially released, it undergoes several revisions later (maybe due to human or technical constraints) - as a result, it may take weeks until the data reaches to a stable value. This so-called 'backfill' phenomenon and its effect on model performance has been barely studied in the prior literature. In this paper, we introduce the multi-variate backfill problem using COVID-19 as the motivating example. We construct a detailed dataset composed of relevant signals over the past year of the "},"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":"2106.04420","kind":"arxiv","version":8},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-06-08T14:48:20Z","cross_cats_sorted":["cs.AI","cs.CY"],"title_canon_sha256":"416870f287f91bdac8194f573f9e12b8485a21b9a39a9b7885b52b04dab1c4bc","abstract_canon_sha256":"420b0fe030f3980678f0d2cf11d667c070095b7189af3a1d9cfca2275990771b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:18:14.843582Z","signature_b64":"n8zQl0kD6v99WgkwyQqOOCKdoY+AQTCsJwBJZDsLy/GFHXdUY5uBGJ6FAhovY9ncrOfhJOPKa7mO7U7ti9qwCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6f59dd11970aa08a868c61c199be9f3a1d709c4cf11d2ee1194b86a65504fbca","last_reissued_at":"2026-07-05T04:18:14.843157Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:18:14.843157Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CY"],"primary_cat":"cs.LG","authors_text":"Alexander Rodr\\'iguez, B. Aditya Prakash, Harshavardhan Kamarthi","submitted_at":"2021-06-08T14:48:20Z","abstract_excerpt":"In real-time forecasting in public health, data collection is a non-trivial and demanding task. Often after initially released, it undergoes several revisions later (maybe due to human or technical constraints) - as a result, it may take weeks until the data reaches to a stable value. This so-called 'backfill' phenomenon and its effect on model performance has been barely studied in the prior literature. In this paper, we introduce the multi-variate backfill problem using COVID-19 as the motivating example. We construct a detailed dataset composed of relevant signals over the past year of the "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.04420","kind":"arxiv","version":8},"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/2106.04420/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":"2106.04420","created_at":"2026-07-05T04:18:14.843210+00:00"},{"alias_kind":"arxiv_version","alias_value":"2106.04420v8","created_at":"2026-07-05T04:18:14.843210+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.04420","created_at":"2026-07-05T04:18:14.843210+00:00"},{"alias_kind":"pith_short_12","alias_value":"N5M52EMXBKQI","created_at":"2026-07-05T04:18:14.843210+00:00"},{"alias_kind":"pith_short_16","alias_value":"N5M52EMXBKQIVBUM","created_at":"2026-07-05T04:18:14.843210+00:00"},{"alias_kind":"pith_short_8","alias_value":"N5M52EMX","created_at":"2026-07-05T04:18:14.843210+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/N5M52EMXBKQIVBUMMHAZTPU7HI","json":"https://pith.science/pith/N5M52EMXBKQIVBUMMHAZTPU7HI.json","graph_json":"https://pith.science/api/pith-number/N5M52EMXBKQIVBUMMHAZTPU7HI/graph.json","events_json":"https://pith.science/api/pith-number/N5M52EMXBKQIVBUMMHAZTPU7HI/events.json","paper":"https://pith.science/paper/N5M52EMX"},"agent_actions":{"view_html":"https://pith.science/pith/N5M52EMXBKQIVBUMMHAZTPU7HI","download_json":"https://pith.science/pith/N5M52EMXBKQIVBUMMHAZTPU7HI.json","view_paper":"https://pith.science/paper/N5M52EMX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2106.04420&json=true","fetch_graph":"https://pith.science/api/pith-number/N5M52EMXBKQIVBUMMHAZTPU7HI/graph.json","fetch_events":"https://pith.science/api/pith-number/N5M52EMXBKQIVBUMMHAZTPU7HI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/N5M52EMXBKQIVBUMMHAZTPU7HI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/N5M52EMXBKQIVBUMMHAZTPU7HI/action/storage_attestation","attest_author":"https://pith.science/pith/N5M52EMXBKQIVBUMMHAZTPU7HI/action/author_attestation","sign_citation":"https://pith.science/pith/N5M52EMXBKQIVBUMMHAZTPU7HI/action/citation_signature","submit_replication":"https://pith.science/pith/N5M52EMXBKQIVBUMMHAZTPU7HI/action/replication_record"}},"created_at":"2026-07-05T04:18:14.843210+00:00","updated_at":"2026-07-05T04:18:14.843210+00:00"}