{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:3MEXAHGQCWYPQAWHZHTCQHKSGT","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":"6bd52bcabf28c3fb31f980ce6d6c68e9e9e720a9a0397be68051944f0ccf2672","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2023-08-25T19:37:18Z","title_canon_sha256":"19a5717ab84be036cf9972477c1500d92a5b52bdc91841392bf8f652752a8c36"},"schema_version":"1.0","source":{"id":"2308.13649","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.13649","created_at":"2026-07-05T06:50:57Z"},{"alias_kind":"arxiv_version","alias_value":"2308.13649v2","created_at":"2026-07-05T06:50:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.13649","created_at":"2026-07-05T06:50:57Z"},{"alias_kind":"pith_short_12","alias_value":"3MEXAHGQCWYP","created_at":"2026-07-05T06:50:57Z"},{"alias_kind":"pith_short_16","alias_value":"3MEXAHGQCWYPQAWH","created_at":"2026-07-05T06:50:57Z"},{"alias_kind":"pith_short_8","alias_value":"3MEXAHGQ","created_at":"2026-07-05T06:50:57Z"}],"graph_snapshots":[{"event_id":"sha256:5ff72ca506233cf00cd26488fb0d7298f1fc8d6e4777fe38d443dc93d873e9fc","target":"graph","created_at":"2026-07-05T06:50:57Z","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/2308.13649/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Annotating biomedical images for supervised learning is a complex and labor-intensive task due to data diversity and its intricate nature. In this paper, we propose an innovative method, the efficient one-pass selective annotation (EPOSA), that significantly reduces the annotation burden while maintaining robust model performance. Our approach employs a variational autoencoder (VAE) to extract salient features from unannotated images, which are subsequently clustered using the DBSCAN algorithm. This process groups similar images together, forming distinct clusters. We then use a two-stage samp","authors_text":"Anqi Feng, Peiyu Duan, Yuan Xue, Yuli Wang, Zhangxing Bian","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2023-08-25T19:37:18Z","title":"Efficient Annotation for Medical Image Analysis: A One-Pass Selective Annotation Approach"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.13649","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":"sha256:9cf8d9c8448b91df7ab022fbce5210fb474c2bc7eb3fb2c6804eab5d9be5dbb0","target":"record","created_at":"2026-07-05T06:50:57Z","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":"6bd52bcabf28c3fb31f980ce6d6c68e9e9e720a9a0397be68051944f0ccf2672","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2023-08-25T19:37:18Z","title_canon_sha256":"19a5717ab84be036cf9972477c1500d92a5b52bdc91841392bf8f652752a8c36"},"schema_version":"1.0","source":{"id":"2308.13649","kind":"arxiv","version":2}},"canonical_sha256":"db09701cd015b0f802c7c9e6281d5234df7b6ad4eb85fcb1aee301259b7c19d5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"db09701cd015b0f802c7c9e6281d5234df7b6ad4eb85fcb1aee301259b7c19d5","first_computed_at":"2026-07-05T06:50:57.878152Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:50:57.878152Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Rw9VHk4vDIWeFWukJkKaQ2eU3yvd7MGWr67STeZPbfL3fYPKb4O0PaESciewQ3Vms0xQXrIEAXnHpjcuW9pdCw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:50:57.878627Z","signed_message":"canonical_sha256_bytes"},"source_id":"2308.13649","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9cf8d9c8448b91df7ab022fbce5210fb474c2bc7eb3fb2c6804eab5d9be5dbb0","sha256:5ff72ca506233cf00cd26488fb0d7298f1fc8d6e4777fe38d443dc93d873e9fc"],"state_sha256":"0be484f378fef7921fb578eaece299a5f74302de8dfd74ec9c473f0370a191b4"}