{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:OBHHHQPF5FI2ZM652BAS6J5I4S","short_pith_number":"pith:OBHHHQPF","schema_version":"1.0","canonical_sha256":"704e73c1e5e951acb3ddd0412f27a8e4850d3d6e5c33e993360cfb023d07357f","source":{"kind":"arxiv","id":"2009.08790","version":2},"attestation_state":"computed","paper":{"title":"Cough Against COVID: Evidence of COVID-19 Signature in Cough Sounds","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.LG","eess.AS"],"primary_cat":"cs.SD","authors_text":"Aman Dalmia, Amrita Mahale, Arsha Nagrani, Jigar Doshi, Neeraj Agarwal, Parag Bhamare, Piyush Bagad, Rahul Panicker, Saurabh Rane","submitted_at":"2020-09-17T14:59:14Z","abstract_excerpt":"Testing capacity for COVID-19 remains a challenge globally due to the lack of adequate supplies, trained personnel, and sample-processing equipment. These problems are even more acute in rural and underdeveloped regions. We demonstrate that solicited-cough sounds collected over a phone, when analysed by our AI model, have statistically significant signal indicative of COVID-19 status (AUC 0.72, t-test,p <0.01,95% CI 0.61-0.83). This holds true for asymptomatic patients as well. Towards this, we collect the largest known(to date) dataset of microbiologically confirmed COVID-19 cough sounds from"},"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":"2009.08790","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.SD","submitted_at":"2020-09-17T14:59:14Z","cross_cats_sorted":["cs.LG","eess.AS"],"title_canon_sha256":"452c4e7007e289d3ac88de60c61bec749b909abee0a260f1e22337654f8dc335","abstract_canon_sha256":"888e766b5356435aa87474507eea1860b812594c15992470af83d331db4e5976"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:37:25.262161Z","signature_b64":"E1HAYcgomDHWIidq1T7HmTLEa772xJayZCL6BZIWoWqnvyxPJK1An1MON3ZhTyMMadH3Srs1i38bfSv/lRhPCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"704e73c1e5e951acb3ddd0412f27a8e4850d3d6e5c33e993360cfb023d07357f","last_reissued_at":"2026-07-05T01:37:25.261691Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:37:25.261691Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Cough Against COVID: Evidence of COVID-19 Signature in Cough Sounds","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.LG","eess.AS"],"primary_cat":"cs.SD","authors_text":"Aman Dalmia, Amrita Mahale, Arsha Nagrani, Jigar Doshi, Neeraj Agarwal, Parag Bhamare, Piyush Bagad, Rahul Panicker, Saurabh Rane","submitted_at":"2020-09-17T14:59:14Z","abstract_excerpt":"Testing capacity for COVID-19 remains a challenge globally due to the lack of adequate supplies, trained personnel, and sample-processing equipment. These problems are even more acute in rural and underdeveloped regions. We demonstrate that solicited-cough sounds collected over a phone, when analysed by our AI model, have statistically significant signal indicative of COVID-19 status (AUC 0.72, t-test,p <0.01,95% CI 0.61-0.83). This holds true for asymptomatic patients as well. Towards this, we collect the largest known(to date) dataset of microbiologically confirmed COVID-19 cough sounds from"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2009.08790","kind":"arxiv","version":2},"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/2009.08790/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":"2009.08790","created_at":"2026-07-05T01:37:25.261746+00:00"},{"alias_kind":"arxiv_version","alias_value":"2009.08790v2","created_at":"2026-07-05T01:37:25.261746+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2009.08790","created_at":"2026-07-05T01:37:25.261746+00:00"},{"alias_kind":"pith_short_12","alias_value":"OBHHHQPF5FI2","created_at":"2026-07-05T01:37:25.261746+00:00"},{"alias_kind":"pith_short_16","alias_value":"OBHHHQPF5FI2ZM65","created_at":"2026-07-05T01:37:25.261746+00:00"},{"alias_kind":"pith_short_8","alias_value":"OBHHHQPF","created_at":"2026-07-05T01:37:25.261746+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2605.28508","citing_title":"Benchmarking AI for low-resource contexts: Thinking beyond leaderboards","ref_index":1,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/OBHHHQPF5FI2ZM652BAS6J5I4S","json":"https://pith.science/pith/OBHHHQPF5FI2ZM652BAS6J5I4S.json","graph_json":"https://pith.science/api/pith-number/OBHHHQPF5FI2ZM652BAS6J5I4S/graph.json","events_json":"https://pith.science/api/pith-number/OBHHHQPF5FI2ZM652BAS6J5I4S/events.json","paper":"https://pith.science/paper/OBHHHQPF"},"agent_actions":{"view_html":"https://pith.science/pith/OBHHHQPF5FI2ZM652BAS6J5I4S","download_json":"https://pith.science/pith/OBHHHQPF5FI2ZM652BAS6J5I4S.json","view_paper":"https://pith.science/paper/OBHHHQPF","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2009.08790&json=true","fetch_graph":"https://pith.science/api/pith-number/OBHHHQPF5FI2ZM652BAS6J5I4S/graph.json","fetch_events":"https://pith.science/api/pith-number/OBHHHQPF5FI2ZM652BAS6J5I4S/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/OBHHHQPF5FI2ZM652BAS6J5I4S/action/timestamp_anchor","attest_storage":"https://pith.science/pith/OBHHHQPF5FI2ZM652BAS6J5I4S/action/storage_attestation","attest_author":"https://pith.science/pith/OBHHHQPF5FI2ZM652BAS6J5I4S/action/author_attestation","sign_citation":"https://pith.science/pith/OBHHHQPF5FI2ZM652BAS6J5I4S/action/citation_signature","submit_replication":"https://pith.science/pith/OBHHHQPF5FI2ZM652BAS6J5I4S/action/replication_record"}},"created_at":"2026-07-05T01:37:25.261746+00:00","updated_at":"2026-07-05T01:37:25.261746+00:00"}