{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:LHM6NSGZ2OWOFBY5YQL4HHECYS","short_pith_number":"pith:LHM6NSGZ","schema_version":"1.0","canonical_sha256":"59d9e6c8d9d3ace2871dc417c39c82c4930e4f02eba6ee14be0ec9720b0fd635","source":{"kind":"arxiv","id":"2506.21641","version":1},"attestation_state":"computed","paper":{"title":"Quantum Variational Transformer Model for Enhanced Cancer Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"q-bio.QM","authors_text":"Don Roosan, Md Rahatul Ashakin, Mohammad Rifat Haider, Rubayat Khan, Saif Nirzhor, Tiffany Khou","submitted_at":"2025-06-25T20:53:40Z","abstract_excerpt":"Accurate prediction of cancer type and primary tumor site is critical for effective diagnosis, personalized treatment, and improved outcomes. Traditional models struggle with the complexity of genomic and clinical data, but quantum computing offers enhanced computational capabilities. This study develops a hybrid quantum-classical transformer model, incorporating quantum attention mechanisms via variational quantum circuits (VQCs) to improve prediction accuracy. Using 30,000 anonymized cancer samples from the Genome Warehouse (GWH), data preprocessing included cleaning, encoding, and feature s"},"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":"2506.21641","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2025-06-25T20:53:40Z","cross_cats_sorted":[],"title_canon_sha256":"cd08430194d69db8323152ade287fe773f29625d6a0962e704febb65abbae48f","abstract_canon_sha256":"f8e7f497267f5d79978fb9f949b9a5e44ed2cb748c3de76e4e67e95ecf5f66ef"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:27:57.847415Z","signature_b64":"3nv9lb8FqLKnRni1xjVYc1dnKNvkCCRkzMdDu2I0zNwft5xJ+ewSXVR/TEKUHFhcwneLR7ivzMEPPZlFE6JWBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"59d9e6c8d9d3ace2871dc417c39c82c4930e4f02eba6ee14be0ec9720b0fd635","last_reissued_at":"2026-07-05T11:27:57.846688Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:27:57.846688Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Quantum Variational Transformer Model for Enhanced Cancer Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"q-bio.QM","authors_text":"Don Roosan, Md Rahatul Ashakin, Mohammad Rifat Haider, Rubayat Khan, Saif Nirzhor, Tiffany Khou","submitted_at":"2025-06-25T20:53:40Z","abstract_excerpt":"Accurate prediction of cancer type and primary tumor site is critical for effective diagnosis, personalized treatment, and improved outcomes. Traditional models struggle with the complexity of genomic and clinical data, but quantum computing offers enhanced computational capabilities. This study develops a hybrid quantum-classical transformer model, incorporating quantum attention mechanisms via variational quantum circuits (VQCs) to improve prediction accuracy. Using 30,000 anonymized cancer samples from the Genome Warehouse (GWH), data preprocessing included cleaning, encoding, and feature s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.21641","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/2506.21641/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":"2506.21641","created_at":"2026-07-05T11:27:57.846792+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.21641v1","created_at":"2026-07-05T11:27:57.846792+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.21641","created_at":"2026-07-05T11:27:57.846792+00:00"},{"alias_kind":"pith_short_12","alias_value":"LHM6NSGZ2OWO","created_at":"2026-07-05T11:27:57.846792+00:00"},{"alias_kind":"pith_short_16","alias_value":"LHM6NSGZ2OWOFBY5","created_at":"2026-07-05T11:27:57.846792+00:00"},{"alias_kind":"pith_short_8","alias_value":"LHM6NSGZ","created_at":"2026-07-05T11:27:57.846792+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/LHM6NSGZ2OWOFBY5YQL4HHECYS","json":"https://pith.science/pith/LHM6NSGZ2OWOFBY5YQL4HHECYS.json","graph_json":"https://pith.science/api/pith-number/LHM6NSGZ2OWOFBY5YQL4HHECYS/graph.json","events_json":"https://pith.science/api/pith-number/LHM6NSGZ2OWOFBY5YQL4HHECYS/events.json","paper":"https://pith.science/paper/LHM6NSGZ"},"agent_actions":{"view_html":"https://pith.science/pith/LHM6NSGZ2OWOFBY5YQL4HHECYS","download_json":"https://pith.science/pith/LHM6NSGZ2OWOFBY5YQL4HHECYS.json","view_paper":"https://pith.science/paper/LHM6NSGZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.21641&json=true","fetch_graph":"https://pith.science/api/pith-number/LHM6NSGZ2OWOFBY5YQL4HHECYS/graph.json","fetch_events":"https://pith.science/api/pith-number/LHM6NSGZ2OWOFBY5YQL4HHECYS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/LHM6NSGZ2OWOFBY5YQL4HHECYS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/LHM6NSGZ2OWOFBY5YQL4HHECYS/action/storage_attestation","attest_author":"https://pith.science/pith/LHM6NSGZ2OWOFBY5YQL4HHECYS/action/author_attestation","sign_citation":"https://pith.science/pith/LHM6NSGZ2OWOFBY5YQL4HHECYS/action/citation_signature","submit_replication":"https://pith.science/pith/LHM6NSGZ2OWOFBY5YQL4HHECYS/action/replication_record"}},"created_at":"2026-07-05T11:27:57.846792+00:00","updated_at":"2026-07-05T11:27:57.846792+00:00"}