{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:NZ4FGYPZ42SCIU7BY72PI7V4JC","short_pith_number":"pith:NZ4FGYPZ","schema_version":"1.0","canonical_sha256":"6e785361f9e6a42453e1c7f4f47ebc48baba03030426ef6dbc6ed75e3952533d","source":{"kind":"arxiv","id":"2306.12754","version":1},"attestation_state":"computed","paper":{"title":"Highly accurate and efficient deep learning paradigm for full-atom protein loop modeling with KarmaLoop","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"q-bio.BM","authors_text":"Chang-Yu Hsieh, Guangyong Chen, Odin Zhang, Peichen Pan, Tianyue Wang, Tingjun Hou, Xujun Zhang, Yu Kang","submitted_at":"2023-06-22T09:16:20Z","abstract_excerpt":"Protein loop modeling is the most challenging yet highly non-trivial task in protein structure prediction. Despite recent progress, existing methods including knowledge-based, ab initio, hybrid and deep learning (DL) methods fall significantly short of either atomic accuracy or computational efficiency. Moreover, an overarching focus on backbone atoms has resulted in a dearth of attention given to side-chain conformation, a critical aspect in a host of downstream applications including ligand docking, molecular dynamics simulation and drug design. To overcome these limitations, we present Karm"},"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":"2306.12754","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.BM","submitted_at":"2023-06-22T09:16:20Z","cross_cats_sorted":[],"title_canon_sha256":"fe3204eb5bd5080e059a205ab9154c61d6d12db663b73175cce245c4cd37cea6","abstract_canon_sha256":"a5c43f69119cf3ebf150f2f60d4cdcdfa58a0d250c5dcbadd62d6c1a1b3225d8"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:23:47.684170Z","signature_b64":"YKE70BVtsVw4IEvCNx3Mdaseycdhuon7oMRlDtzTwCn3kofhP4FBt/cQdzio3e7pf5Klofczpk9TGPRKyjY/Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6e785361f9e6a42453e1c7f4f47ebc48baba03030426ef6dbc6ed75e3952533d","last_reissued_at":"2026-07-05T06:23:47.683718Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:23:47.683718Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Highly accurate and efficient deep learning paradigm for full-atom protein loop modeling with KarmaLoop","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"q-bio.BM","authors_text":"Chang-Yu Hsieh, Guangyong Chen, Odin Zhang, Peichen Pan, Tianyue Wang, Tingjun Hou, Xujun Zhang, Yu Kang","submitted_at":"2023-06-22T09:16:20Z","abstract_excerpt":"Protein loop modeling is the most challenging yet highly non-trivial task in protein structure prediction. Despite recent progress, existing methods including knowledge-based, ab initio, hybrid and deep learning (DL) methods fall significantly short of either atomic accuracy or computational efficiency. Moreover, an overarching focus on backbone atoms has resulted in a dearth of attention given to side-chain conformation, a critical aspect in a host of downstream applications including ligand docking, molecular dynamics simulation and drug design. To overcome these limitations, we present Karm"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.12754","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/2306.12754/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":"2306.12754","created_at":"2026-07-05T06:23:47.683777+00:00"},{"alias_kind":"arxiv_version","alias_value":"2306.12754v1","created_at":"2026-07-05T06:23:47.683777+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.12754","created_at":"2026-07-05T06:23:47.683777+00:00"},{"alias_kind":"pith_short_12","alias_value":"NZ4FGYPZ42SC","created_at":"2026-07-05T06:23:47.683777+00:00"},{"alias_kind":"pith_short_16","alias_value":"NZ4FGYPZ42SCIU7B","created_at":"2026-07-05T06:23:47.683777+00:00"},{"alias_kind":"pith_short_8","alias_value":"NZ4FGYPZ","created_at":"2026-07-05T06:23:47.683777+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/NZ4FGYPZ42SCIU7BY72PI7V4JC","json":"https://pith.science/pith/NZ4FGYPZ42SCIU7BY72PI7V4JC.json","graph_json":"https://pith.science/api/pith-number/NZ4FGYPZ42SCIU7BY72PI7V4JC/graph.json","events_json":"https://pith.science/api/pith-number/NZ4FGYPZ42SCIU7BY72PI7V4JC/events.json","paper":"https://pith.science/paper/NZ4FGYPZ"},"agent_actions":{"view_html":"https://pith.science/pith/NZ4FGYPZ42SCIU7BY72PI7V4JC","download_json":"https://pith.science/pith/NZ4FGYPZ42SCIU7BY72PI7V4JC.json","view_paper":"https://pith.science/paper/NZ4FGYPZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2306.12754&json=true","fetch_graph":"https://pith.science/api/pith-number/NZ4FGYPZ42SCIU7BY72PI7V4JC/graph.json","fetch_events":"https://pith.science/api/pith-number/NZ4FGYPZ42SCIU7BY72PI7V4JC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/NZ4FGYPZ42SCIU7BY72PI7V4JC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/NZ4FGYPZ42SCIU7BY72PI7V4JC/action/storage_attestation","attest_author":"https://pith.science/pith/NZ4FGYPZ42SCIU7BY72PI7V4JC/action/author_attestation","sign_citation":"https://pith.science/pith/NZ4FGYPZ42SCIU7BY72PI7V4JC/action/citation_signature","submit_replication":"https://pith.science/pith/NZ4FGYPZ42SCIU7BY72PI7V4JC/action/replication_record"}},"created_at":"2026-07-05T06:23:47.683777+00:00","updated_at":"2026-07-05T06:23:47.683777+00:00"}