{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:S65PPYYTGY22CYJHHEFCYIQL3W","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"7a5acfa74ed49e35beca8955a1b2695111496b93e57b738dbe7577142d35734a","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2021-07-10T10:39:18Z","title_canon_sha256":"92e5af1555867f63a4f0c341e7f0cddca3f5d6e66745b099f60cd84ef6a6cce5"},"schema_version":"1.0","source":{"id":"2107.04808","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2107.04808","created_at":"2026-07-05T08:00:29Z"},{"alias_kind":"arxiv_version","alias_value":"2107.04808v2","created_at":"2026-07-05T08:00:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2107.04808","created_at":"2026-07-05T08:00:29Z"},{"alias_kind":"pith_short_12","alias_value":"S65PPYYTGY22","created_at":"2026-07-05T08:00:29Z"},{"alias_kind":"pith_short_16","alias_value":"S65PPYYTGY22CYJH","created_at":"2026-07-05T08:00:29Z"},{"alias_kind":"pith_short_8","alias_value":"S65PPYYT","created_at":"2026-07-05T08:00:29Z"}],"graph_snapshots":[{"event_id":"sha256:479fdb4f04207b5a391aee3193ba25e0f14dd5eb5da91c18315e70f3801b95a0","target":"graph","created_at":"2026-07-05T08:00:29Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2107.04808/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The paper presents a comparative analysis of three distinct approaches based on deep learning for COVID-19 detection in chest CTs. The first approach is a volumetric one, involving 3D convolutions, while the other two approaches perform at first slice-wise classification and then aggregate the results at the volume level. The experiments are carried on the COV19-CT-DB dataset, with the aim of addressing the challenge raised by the MIA-COV19D Competition within ICCV 2021. Our best results on the validation subset reach a macro-F1 score of 0.92, which improves considerably the baseline score of ","authors_text":"Cosmin Moisii, Mihaela Breaban, Radu Miron, Sergiu Dinu","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2021-07-10T10:39:18Z","title":"COVID Detection in Chest CTs: Improving the Baseline on COV19-CT-DB"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2107.04808","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:d6036eea41985256a0835fac5ecc69be1d300803f303b90e7c0afde666880afb","target":"record","created_at":"2026-07-05T08:00:29Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"7a5acfa74ed49e35beca8955a1b2695111496b93e57b738dbe7577142d35734a","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2021-07-10T10:39:18Z","title_canon_sha256":"92e5af1555867f63a4f0c341e7f0cddca3f5d6e66745b099f60cd84ef6a6cce5"},"schema_version":"1.0","source":{"id":"2107.04808","kind":"arxiv","version":2}},"canonical_sha256":"97baf7e3133635a16127390a2c220bdd9f95f4e660b40836c6390a6417e5718c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"97baf7e3133635a16127390a2c220bdd9f95f4e660b40836c6390a6417e5718c","first_computed_at":"2026-07-05T08:00:29.493628Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:00:29.493628Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Xeqpc68rVK3BmVsp8vNvqY+TXV9KzMTGB8207B5FvTx94sCn8LfMw5QYFGWEQYJV5wXSBxB422GPKFSuuudWDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:00:29.494087Z","signed_message":"canonical_sha256_bytes"},"source_id":"2107.04808","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d6036eea41985256a0835fac5ecc69be1d300803f303b90e7c0afde666880afb","sha256:479fdb4f04207b5a391aee3193ba25e0f14dd5eb5da91c18315e70f3801b95a0"],"state_sha256":"fcffc6e7e31484a9628818b2308f71d6d172ac13d04489afa3c95b77b7a524d8"}