{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:A7PXFETAXEKC2ZLO3CPTI7UMW7","short_pith_number":"pith:A7PXFETA","schema_version":"1.0","canonical_sha256":"07df729260b9142d656ed89f347e8cb7db3caf7e4be63122afc1e31f042ffa0b","source":{"kind":"arxiv","id":"2507.19755","version":1},"attestation_state":"computed","paper":{"title":"Modeling enzyme temperature stability from sequence segment perspective","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","q-bio.BM","q-bio.QM"],"primary_cat":"cs.LG","authors_text":"Fengshan Zhang, Hongbin Shen, Jing Wu, Lei Wang, Longbing Cao, Runze Yang, Shiheng Chen, Wei Zhang, Xiaoyong Pan, Zhanzhi Liu, Zhaohong Deng, Zhisheng Wei, Ziqi Zhang","submitted_at":"2025-07-26T03:01:58Z","abstract_excerpt":"Developing enzymes with desired thermal properties is crucial for a wide range of industrial and research applications, and determining temperature stability is an essential step in this process. Experimental determination of thermal parameters is labor-intensive, time-consuming, and costly. Moreover, existing computational approaches are often hindered by limited data availability and imbalanced distributions. To address these challenges, we introduce a curated temperature stability dataset designed for model development and benchmarking in enzyme thermal modeling. Leveraging this dataset, we"},"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":"2507.19755","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-26T03:01:58Z","cross_cats_sorted":["cs.AI","q-bio.BM","q-bio.QM"],"title_canon_sha256":"49ba0656da70a1c57ea2f17069a4894d3e4cfed6c80099ee334df57a132165b0","abstract_canon_sha256":"8fdb2f5fd312744ba36f3126ab33f5396d2d4a25e8312e7c6b6ee284ed5c9379"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:43:41.274781Z","signature_b64":"wgab8mnJlemtxnR+Js+qKRKpz+AiqLn82iD/WOUwPRRfrJRhVpAWMLso/Hskz9D55d6J+3aAEafG/+bdj7yHCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"07df729260b9142d656ed89f347e8cb7db3caf7e4be63122afc1e31f042ffa0b","last_reissued_at":"2026-07-05T11:43:41.274365Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:43:41.274365Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Modeling enzyme temperature stability from sequence segment perspective","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","q-bio.BM","q-bio.QM"],"primary_cat":"cs.LG","authors_text":"Fengshan Zhang, Hongbin Shen, Jing Wu, Lei Wang, Longbing Cao, Runze Yang, Shiheng Chen, Wei Zhang, Xiaoyong Pan, Zhanzhi Liu, Zhaohong Deng, Zhisheng Wei, Ziqi Zhang","submitted_at":"2025-07-26T03:01:58Z","abstract_excerpt":"Developing enzymes with desired thermal properties is crucial for a wide range of industrial and research applications, and determining temperature stability is an essential step in this process. Experimental determination of thermal parameters is labor-intensive, time-consuming, and costly. Moreover, existing computational approaches are often hindered by limited data availability and imbalanced distributions. To address these challenges, we introduce a curated temperature stability dataset designed for model development and benchmarking in enzyme thermal modeling. Leveraging this dataset, we"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.19755","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/2507.19755/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":"2507.19755","created_at":"2026-07-05T11:43:41.274429+00:00"},{"alias_kind":"arxiv_version","alias_value":"2507.19755v1","created_at":"2026-07-05T11:43:41.274429+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.19755","created_at":"2026-07-05T11:43:41.274429+00:00"},{"alias_kind":"pith_short_12","alias_value":"A7PXFETAXEKC","created_at":"2026-07-05T11:43:41.274429+00:00"},{"alias_kind":"pith_short_16","alias_value":"A7PXFETAXEKC2ZLO","created_at":"2026-07-05T11:43:41.274429+00:00"},{"alias_kind":"pith_short_8","alias_value":"A7PXFETA","created_at":"2026-07-05T11:43:41.274429+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/A7PXFETAXEKC2ZLO3CPTI7UMW7","json":"https://pith.science/pith/A7PXFETAXEKC2ZLO3CPTI7UMW7.json","graph_json":"https://pith.science/api/pith-number/A7PXFETAXEKC2ZLO3CPTI7UMW7/graph.json","events_json":"https://pith.science/api/pith-number/A7PXFETAXEKC2ZLO3CPTI7UMW7/events.json","paper":"https://pith.science/paper/A7PXFETA"},"agent_actions":{"view_html":"https://pith.science/pith/A7PXFETAXEKC2ZLO3CPTI7UMW7","download_json":"https://pith.science/pith/A7PXFETAXEKC2ZLO3CPTI7UMW7.json","view_paper":"https://pith.science/paper/A7PXFETA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2507.19755&json=true","fetch_graph":"https://pith.science/api/pith-number/A7PXFETAXEKC2ZLO3CPTI7UMW7/graph.json","fetch_events":"https://pith.science/api/pith-number/A7PXFETAXEKC2ZLO3CPTI7UMW7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/A7PXFETAXEKC2ZLO3CPTI7UMW7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/A7PXFETAXEKC2ZLO3CPTI7UMW7/action/storage_attestation","attest_author":"https://pith.science/pith/A7PXFETAXEKC2ZLO3CPTI7UMW7/action/author_attestation","sign_citation":"https://pith.science/pith/A7PXFETAXEKC2ZLO3CPTI7UMW7/action/citation_signature","submit_replication":"https://pith.science/pith/A7PXFETAXEKC2ZLO3CPTI7UMW7/action/replication_record"}},"created_at":"2026-07-05T11:43:41.274429+00:00","updated_at":"2026-07-05T11:43:41.274429+00:00"}