{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:7JUJTM3BDSI5AFRVCNCG7JSQKG","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":"31fb7d216c3a95aa2bd37596c007e1b5c9836c47e1b48c722099735d63a0fa4e","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-01-18T17:25:55Z","title_canon_sha256":"8010d9a70fd1673a34a73c1bcc84810ef6958e59fe4a456a56e5ee21f78dcc1f"},"schema_version":"1.0","source":{"id":"2301.07670","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.07670","created_at":"2026-07-05T06:49:01Z"},{"alias_kind":"arxiv_version","alias_value":"2301.07670v2","created_at":"2026-07-05T06:49:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.07670","created_at":"2026-07-05T06:49:01Z"},{"alias_kind":"pith_short_12","alias_value":"7JUJTM3BDSI5","created_at":"2026-07-05T06:49:01Z"},{"alias_kind":"pith_short_16","alias_value":"7JUJTM3BDSI5AFRV","created_at":"2026-07-05T06:49:01Z"},{"alias_kind":"pith_short_8","alias_value":"7JUJTM3B","created_at":"2026-07-05T06:49:01Z"}],"graph_snapshots":[{"event_id":"sha256:503619138c22a227f4f5f1803ea719867048caf1f80fafc22d1e135262ebed2c","target":"graph","created_at":"2026-07-05T06:49:01Z","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/2301.07670/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The performance of learning-based algorithms improves with the amount of labelled data used for training. Yet, manually annotating data is particularly difficult for medical image segmentation tasks because of the limited expert availability and intensive manual effort required. To reduce manual labelling, active learning (AL) targets the most informative samples from the unlabelled set to annotate and add to the labelled training set. On the one hand, most active learning works have focused on the classification or limited segmentation of natural images, despite active learning being highly d","authors_text":"Christian Desrosiers, Herv\\'e Lombaert, M\\'elanie Gaillochet","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-01-18T17:25:55Z","title":"Active learning for medical image segmentation with stochastic batches"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.07670","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":"sha256:65f1b2702e6d1ffd7500e7b09042c5a7c2758ef1fb4cf7491749382bc77118f7","target":"record","created_at":"2026-07-05T06:49:01Z","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":"31fb7d216c3a95aa2bd37596c007e1b5c9836c47e1b48c722099735d63a0fa4e","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-01-18T17:25:55Z","title_canon_sha256":"8010d9a70fd1673a34a73c1bcc84810ef6958e59fe4a456a56e5ee21f78dcc1f"},"schema_version":"1.0","source":{"id":"2301.07670","kind":"arxiv","version":2}},"canonical_sha256":"fa6899b3611c91d0163513446fa65051b738799b63c9b1b1e80e6f8c2a07c2bf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fa6899b3611c91d0163513446fa65051b738799b63c9b1b1e80e6f8c2a07c2bf","first_computed_at":"2026-07-05T06:49:01.752081Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:49:01.752081Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7wNWBJNfjCgOqY7k1b6sBNMfxZnYVXUaEbLQRHV/gDiuDAjU8sEXj60iJyYKrs+UymVkzp2UVf68Pa2jL03vBg==","signature_status":"signed_v1","signed_at":"2026-07-05T06:49:01.752522Z","signed_message":"canonical_sha256_bytes"},"source_id":"2301.07670","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:65f1b2702e6d1ffd7500e7b09042c5a7c2758ef1fb4cf7491749382bc77118f7","sha256:503619138c22a227f4f5f1803ea719867048caf1f80fafc22d1e135262ebed2c"],"state_sha256":"e6a24f50d3942554dc44a878f263449bbe9e0e94123e33747437a11e09356071"}