{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:DLUFUFHKYV7ZONMK4DDCEZGDQ7","short_pith_number":"pith:DLUFUFHK","schema_version":"1.0","canonical_sha256":"1ae85a14eac57f97358ae0c62264c387e79dec60c9924a15e28a30425b691f49","source":{"kind":"arxiv","id":"1911.03044","version":2},"attestation_state":"computed","paper":{"title":"AITom: Open-source AI platform for cryo-electron tomography data analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","eess.IV"],"primary_cat":"q-bio.QM","authors_text":"Min Xu, Xiangrui Zeng","submitted_at":"2019-11-08T04:33:18Z","abstract_excerpt":"Cryo-electron tomography (cryo-ET) is an emerging technology for the 3D visualization of structural organizations and interactions of subcellular components at near-native state and sub-molecular resolution. Tomograms captured by cryo-ET contain heterogeneous structures representing the complex and dynamic subcellular environment. Since the structures are not purified or fluorescently labeled, the spatial organization and interaction between both the known and unknown structures can be studied in their native environment. The rapid advances of cryo-electron tomography (cryo-ET) have generated "},"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":"1911.03044","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2019-11-08T04:33:18Z","cross_cats_sorted":["cs.LG","eess.IV"],"title_canon_sha256":"fd96cba86c7b439a83214ab770809244c70cb43f5f6f19e17e34d0fab67a60d1","abstract_canon_sha256":"befa23b838be4c74d099f2ee4acef23a10ecf02e6bc5d73e8603f7e1cfc338bb"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:47:42.271528Z","signature_b64":"9Ki88XfPaRa/tklAGP7sgM4SE92kF0wD9rsaRijFPQ31S3z84DFle/UJxJsfXKVoKc24YrzIPib0B0Lp4wWUBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1ae85a14eac57f97358ae0c62264c387e79dec60c9924a15e28a30425b691f49","last_reissued_at":"2026-07-05T01:47:42.271044Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:47:42.271044Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"AITom: Open-source AI platform for cryo-electron tomography data analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","eess.IV"],"primary_cat":"q-bio.QM","authors_text":"Min Xu, Xiangrui Zeng","submitted_at":"2019-11-08T04:33:18Z","abstract_excerpt":"Cryo-electron tomography (cryo-ET) is an emerging technology for the 3D visualization of structural organizations and interactions of subcellular components at near-native state and sub-molecular resolution. Tomograms captured by cryo-ET contain heterogeneous structures representing the complex and dynamic subcellular environment. Since the structures are not purified or fluorescently labeled, the spatial organization and interaction between both the known and unknown structures can be studied in their native environment. The rapid advances of cryo-electron tomography (cryo-ET) have generated "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1911.03044","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/1911.03044/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":"1911.03044","created_at":"2026-07-05T01:47:42.271109+00:00"},{"alias_kind":"arxiv_version","alias_value":"1911.03044v2","created_at":"2026-07-05T01:47:42.271109+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1911.03044","created_at":"2026-07-05T01:47:42.271109+00:00"},{"alias_kind":"pith_short_12","alias_value":"DLUFUFHKYV7Z","created_at":"2026-07-05T01:47:42.271109+00:00"},{"alias_kind":"pith_short_16","alias_value":"DLUFUFHKYV7ZONMK","created_at":"2026-07-05T01:47:42.271109+00:00"},{"alias_kind":"pith_short_8","alias_value":"DLUFUFHK","created_at":"2026-07-05T01:47:42.271109+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/DLUFUFHKYV7ZONMK4DDCEZGDQ7","json":"https://pith.science/pith/DLUFUFHKYV7ZONMK4DDCEZGDQ7.json","graph_json":"https://pith.science/api/pith-number/DLUFUFHKYV7ZONMK4DDCEZGDQ7/graph.json","events_json":"https://pith.science/api/pith-number/DLUFUFHKYV7ZONMK4DDCEZGDQ7/events.json","paper":"https://pith.science/paper/DLUFUFHK"},"agent_actions":{"view_html":"https://pith.science/pith/DLUFUFHKYV7ZONMK4DDCEZGDQ7","download_json":"https://pith.science/pith/DLUFUFHKYV7ZONMK4DDCEZGDQ7.json","view_paper":"https://pith.science/paper/DLUFUFHK","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1911.03044&json=true","fetch_graph":"https://pith.science/api/pith-number/DLUFUFHKYV7ZONMK4DDCEZGDQ7/graph.json","fetch_events":"https://pith.science/api/pith-number/DLUFUFHKYV7ZONMK4DDCEZGDQ7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/DLUFUFHKYV7ZONMK4DDCEZGDQ7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/DLUFUFHKYV7ZONMK4DDCEZGDQ7/action/storage_attestation","attest_author":"https://pith.science/pith/DLUFUFHKYV7ZONMK4DDCEZGDQ7/action/author_attestation","sign_citation":"https://pith.science/pith/DLUFUFHKYV7ZONMK4DDCEZGDQ7/action/citation_signature","submit_replication":"https://pith.science/pith/DLUFUFHKYV7ZONMK4DDCEZGDQ7/action/replication_record"}},"created_at":"2026-07-05T01:47:42.271109+00:00","updated_at":"2026-07-05T01:47:42.271109+00:00"}