{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:SOQFRPXJN3U5UFNFBSIW3MFLY5","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"320da7c000d8b73ff7301dd50aa3eaf09b6c7051a2c25005913d4cdfec035b29","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-09-02T22:20:46Z","title_canon_sha256":"b24e327269161b3b3a485caddd6e91da1f560c362558854cbf225bc6c6b03e57"},"schema_version":"1.0","source":{"id":"2509.02863","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.02863","created_at":"2026-07-05T12:03:58Z"},{"alias_kind":"arxiv_version","alias_value":"2509.02863v1","created_at":"2026-07-05T12:03:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.02863","created_at":"2026-07-05T12:03:58Z"},{"alias_kind":"pith_short_12","alias_value":"SOQFRPXJN3U5","created_at":"2026-07-05T12:03:58Z"},{"alias_kind":"pith_short_16","alias_value":"SOQFRPXJN3U5UFNF","created_at":"2026-07-05T12:03:58Z"},{"alias_kind":"pith_short_8","alias_value":"SOQFRPXJ","created_at":"2026-07-05T12:03:58Z"}],"graph_snapshots":[{"event_id":"sha256:acbeaa47a9546985aff207e0fa1a32a29368c02ef08e9399e8d78e3d3f0129f8","target":"graph","created_at":"2026-07-05T12:03:58Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2509.02863/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Class imbalance remains a critical challenge in machine learning (ML), particularly in the medical domain, where underrepresented minority classes lead to biased models and reduced predictive performance. This study introduces Quantum-Inspired SMOTE (QI-SMOTE), a novel data augmentation technique that enhances the performance of ML classifiers, including Random Forest (RF), Support Vector Machine (SVM), Logistic Regression (LR), k-Nearest Neighbors (KNN), Gradient Boosting (GB), and Neural Networks, by leveraging quantum principles such as quantum evolution and layered entanglement. Unlike con","authors_text":"Pardeep Singh, Vikas Kashtriya","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-09-02T22:20:46Z","title":"Enhancing Machine Learning for Imbalanced Medical Data: A Quantum-Inspired Approach to Synthetic Oversampling (QI-SMOTE)"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.02863","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:8296681fc195bcfc5db738317c9a50afe4eb57e9d569fceb7cbb76592ab88592","target":"record","created_at":"2026-07-05T12:03:58Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"320da7c000d8b73ff7301dd50aa3eaf09b6c7051a2c25005913d4cdfec035b29","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-09-02T22:20:46Z","title_canon_sha256":"b24e327269161b3b3a485caddd6e91da1f560c362558854cbf225bc6c6b03e57"},"schema_version":"1.0","source":{"id":"2509.02863","kind":"arxiv","version":1}},"canonical_sha256":"93a058bee96ee9da15a50c916db0abc75f3b35ce04bae0d8617cd1aac8cc75b3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"93a058bee96ee9da15a50c916db0abc75f3b35ce04bae0d8617cd1aac8cc75b3","first_computed_at":"2026-07-05T12:03:58.734123Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:03:58.734123Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HLgVU5wmPyQD06S0ZhL12/CUYkq8/5/t5HHfgYN4InpIX6tQZs2l8FN+/FncxXxOmRT78HHYchS7cD2Yg40HCg==","signature_status":"signed_v1","signed_at":"2026-07-05T12:03:58.734724Z","signed_message":"canonical_sha256_bytes"},"source_id":"2509.02863","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8296681fc195bcfc5db738317c9a50afe4eb57e9d569fceb7cbb76592ab88592","sha256:acbeaa47a9546985aff207e0fa1a32a29368c02ef08e9399e8d78e3d3f0129f8"],"state_sha256":"6458e37c9194a4f2da327b84a1daa4fa18ac478206b29b948a5c7db29f1ec134"}