{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:EVVH7WIK2RFAOCZINRMX6VMS4H","short_pith_number":"pith:EVVH7WIK","schema_version":"1.0","canonical_sha256":"256a7fd90ad44a070b286c597f5592e1d6373fc825cbb4bd49345e3566d2a3dd","source":{"kind":"arxiv","id":"2311.11004","version":1},"attestation_state":"computed","paper":{"title":"A Foundation Model for Cell Segmentation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"q-bio.QM","authors_text":"Alexander Pearson-Goulart, David Van Valen, Edward Pao, Elora Pradhan, Georgia Gkioxari, Markus Marks, Morgan Schwartz, Pietro Perona, Qilin Li, Rohit Dilip, Ross Barnowski, Shenyi Li, Uriah Israel, Yisong Yue","submitted_at":"2023-11-18T07:55:09Z","abstract_excerpt":"Cells are the fundamental unit of biological organization, and identifying them in imaging data - cell segmentation - is a critical task for various cellular imaging experiments. While deep learning methods have led to substantial progress on this problem, models that have seen wide use are specialist models that work well for specific domains. Methods that have learned the general notion of \"what is a cell\" and can identify them across different domains of cellular imaging data have proven elusive. In this work, we present CellSAM, a foundation model for cell segmentation that generalizes acr"},"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":"2311.11004","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-bio.QM","submitted_at":"2023-11-18T07:55:09Z","cross_cats_sorted":[],"title_canon_sha256":"36f06c3aeddfacd2da0ead0d5d60dbcbd52632bfc2c25a6179eff64e2fb7c75e","abstract_canon_sha256":"af816cd30fb85f3e4b316c729d0be9bf2a934a6f2c0c5366eb3225be3c9235e5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:14:26.390628Z","signature_b64":"rI8vFXmq9szXss0KXALIYwtLagm+AEDvYo3TClHlEyVMG32YbI8LCmWgRH2ZQ1j7J+rteBwvyEnJdEA1XnxDCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"256a7fd90ad44a070b286c597f5592e1d6373fc825cbb4bd49345e3566d2a3dd","last_reissued_at":"2026-07-05T07:14:26.390139Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:14:26.390139Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Foundation Model for Cell Segmentation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"q-bio.QM","authors_text":"Alexander Pearson-Goulart, David Van Valen, Edward Pao, Elora Pradhan, Georgia Gkioxari, Markus Marks, Morgan Schwartz, Pietro Perona, Qilin Li, Rohit Dilip, Ross Barnowski, Shenyi Li, Uriah Israel, Yisong Yue","submitted_at":"2023-11-18T07:55:09Z","abstract_excerpt":"Cells are the fundamental unit of biological organization, and identifying them in imaging data - cell segmentation - is a critical task for various cellular imaging experiments. While deep learning methods have led to substantial progress on this problem, models that have seen wide use are specialist models that work well for specific domains. Methods that have learned the general notion of \"what is a cell\" and can identify them across different domains of cellular imaging data have proven elusive. In this work, we present CellSAM, a foundation model for cell segmentation that generalizes acr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.11004","kind":"arxiv","version":1},"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/2311.11004/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":"2311.11004","created_at":"2026-07-05T07:14:26.390198+00:00"},{"alias_kind":"arxiv_version","alias_value":"2311.11004v1","created_at":"2026-07-05T07:14:26.390198+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.11004","created_at":"2026-07-05T07:14:26.390198+00:00"},{"alias_kind":"pith_short_12","alias_value":"EVVH7WIK2RFA","created_at":"2026-07-05T07:14:26.390198+00:00"},{"alias_kind":"pith_short_16","alias_value":"EVVH7WIK2RFAOCZI","created_at":"2026-07-05T07:14:26.390198+00:00"},{"alias_kind":"pith_short_8","alias_value":"EVVH7WIK","created_at":"2026-07-05T07:14:26.390198+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/EVVH7WIK2RFAOCZINRMX6VMS4H","json":"https://pith.science/pith/EVVH7WIK2RFAOCZINRMX6VMS4H.json","graph_json":"https://pith.science/api/pith-number/EVVH7WIK2RFAOCZINRMX6VMS4H/graph.json","events_json":"https://pith.science/api/pith-number/EVVH7WIK2RFAOCZINRMX6VMS4H/events.json","paper":"https://pith.science/paper/EVVH7WIK"},"agent_actions":{"view_html":"https://pith.science/pith/EVVH7WIK2RFAOCZINRMX6VMS4H","download_json":"https://pith.science/pith/EVVH7WIK2RFAOCZINRMX6VMS4H.json","view_paper":"https://pith.science/paper/EVVH7WIK","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2311.11004&json=true","fetch_graph":"https://pith.science/api/pith-number/EVVH7WIK2RFAOCZINRMX6VMS4H/graph.json","fetch_events":"https://pith.science/api/pith-number/EVVH7WIK2RFAOCZINRMX6VMS4H/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/EVVH7WIK2RFAOCZINRMX6VMS4H/action/timestamp_anchor","attest_storage":"https://pith.science/pith/EVVH7WIK2RFAOCZINRMX6VMS4H/action/storage_attestation","attest_author":"https://pith.science/pith/EVVH7WIK2RFAOCZINRMX6VMS4H/action/author_attestation","sign_citation":"https://pith.science/pith/EVVH7WIK2RFAOCZINRMX6VMS4H/action/citation_signature","submit_replication":"https://pith.science/pith/EVVH7WIK2RFAOCZINRMX6VMS4H/action/replication_record"}},"created_at":"2026-07-05T07:14:26.390198+00:00","updated_at":"2026-07-05T07:14:26.390198+00:00"}