{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:4XLWEFWV3VCZZ5CRB3QJHS3SHJ","short_pith_number":"pith:4XLWEFWV","schema_version":"1.0","canonical_sha256":"e5d76216d5dd459cf4510ee093cb723a6b40c030477e5af80dd1b59842d4e321","source":{"kind":"arxiv","id":"2107.01331","version":1},"attestation_state":"computed","paper":{"title":"Exploring generative atomic models in cryo-EM reconstruction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"q-bio.BM","authors_text":"Adam Lerer, Bonnie Berger, Ellen D. Zhong, Joseph H. Davis","submitted_at":"2021-07-03T03:06:26Z","abstract_excerpt":"Cryo-EM reconstruction algorithms seek to determine a molecule's 3D density map from a series of noisy, unlabeled 2D projection images captured with an electron microscope. Although reconstruction algorithms typically model the 3D volume as a generic function parameterized as a voxel array or neural network, the underlying atomic structure of the protein of interest places well-defined physical constraints on the reconstructed structure. In this work, we exploit prior information provided by an atomic model to reconstruct distributions of 3D structures from a cryo-EM dataset. We propose Cryofo"},"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":"2107.01331","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-bio.BM","submitted_at":"2021-07-03T03:06:26Z","cross_cats_sorted":[],"title_canon_sha256":"60896fa5d1e3599cacd847e8b293883248d15b05561edda2ae7ae11942682cc8","abstract_canon_sha256":"dcc412d271c2ec33bfc523cc367db2b030c79709d2d583b90b259d8c7ca0f07b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:54:42.046405Z","signature_b64":"adUE41FZuzs6qtYy/O0jyfJ+vLMDsoSzvVm6nXwjquKf5VJAaq9UDirJchQZ1jzkMySIWUcIaHFmsqj4BUGvAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e5d76216d5dd459cf4510ee093cb723a6b40c030477e5af80dd1b59842d4e321","last_reissued_at":"2026-07-05T02:54:42.045932Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:54:42.045932Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Exploring generative atomic models in cryo-EM reconstruction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"q-bio.BM","authors_text":"Adam Lerer, Bonnie Berger, Ellen D. Zhong, Joseph H. Davis","submitted_at":"2021-07-03T03:06:26Z","abstract_excerpt":"Cryo-EM reconstruction algorithms seek to determine a molecule's 3D density map from a series of noisy, unlabeled 2D projection images captured with an electron microscope. Although reconstruction algorithms typically model the 3D volume as a generic function parameterized as a voxel array or neural network, the underlying atomic structure of the protein of interest places well-defined physical constraints on the reconstructed structure. In this work, we exploit prior information provided by an atomic model to reconstruct distributions of 3D structures from a cryo-EM dataset. We propose Cryofo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2107.01331","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/2107.01331/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":"2107.01331","created_at":"2026-07-05T02:54:42.045991+00:00"},{"alias_kind":"arxiv_version","alias_value":"2107.01331v1","created_at":"2026-07-05T02:54:42.045991+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2107.01331","created_at":"2026-07-05T02:54:42.045991+00:00"},{"alias_kind":"pith_short_12","alias_value":"4XLWEFWV3VCZ","created_at":"2026-07-05T02:54:42.045991+00:00"},{"alias_kind":"pith_short_16","alias_value":"4XLWEFWV3VCZZ5CR","created_at":"2026-07-05T02:54:42.045991+00:00"},{"alias_kind":"pith_short_8","alias_value":"4XLWEFWV","created_at":"2026-07-05T02:54:42.045991+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/4XLWEFWV3VCZZ5CRB3QJHS3SHJ","json":"https://pith.science/pith/4XLWEFWV3VCZZ5CRB3QJHS3SHJ.json","graph_json":"https://pith.science/api/pith-number/4XLWEFWV3VCZZ5CRB3QJHS3SHJ/graph.json","events_json":"https://pith.science/api/pith-number/4XLWEFWV3VCZZ5CRB3QJHS3SHJ/events.json","paper":"https://pith.science/paper/4XLWEFWV"},"agent_actions":{"view_html":"https://pith.science/pith/4XLWEFWV3VCZZ5CRB3QJHS3SHJ","download_json":"https://pith.science/pith/4XLWEFWV3VCZZ5CRB3QJHS3SHJ.json","view_paper":"https://pith.science/paper/4XLWEFWV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2107.01331&json=true","fetch_graph":"https://pith.science/api/pith-number/4XLWEFWV3VCZZ5CRB3QJHS3SHJ/graph.json","fetch_events":"https://pith.science/api/pith-number/4XLWEFWV3VCZZ5CRB3QJHS3SHJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/4XLWEFWV3VCZZ5CRB3QJHS3SHJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/4XLWEFWV3VCZZ5CRB3QJHS3SHJ/action/storage_attestation","attest_author":"https://pith.science/pith/4XLWEFWV3VCZZ5CRB3QJHS3SHJ/action/author_attestation","sign_citation":"https://pith.science/pith/4XLWEFWV3VCZZ5CRB3QJHS3SHJ/action/citation_signature","submit_replication":"https://pith.science/pith/4XLWEFWV3VCZZ5CRB3QJHS3SHJ/action/replication_record"}},"created_at":"2026-07-05T02:54:42.045991+00:00","updated_at":"2026-07-05T02:54:42.045991+00:00"}