{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:XQLYIPHRBKACDRZPJQSXHIT3U2","short_pith_number":"pith:XQLYIPHR","canonical_record":{"source":{"id":"2506.19973","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2025-06-24T19:40:39Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"3bbda363df06fb043d4e5cf0fc448e56ed3f797dbfcad6fb180edb15e679d166","abstract_canon_sha256":"76ef1d934d277a9f65c140934a860f056b1f2c3f86561641a99656817350f434"},"schema_version":"1.0"},"canonical_sha256":"bc17843cf10a8021c72f4c2573a27ba6b992dac2b2e576587827f61161059330","source":{"kind":"arxiv","id":"2506.19973","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.19973","created_at":"2026-07-05T11:26:57Z"},{"alias_kind":"arxiv_version","alias_value":"2506.19973v1","created_at":"2026-07-05T11:26:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.19973","created_at":"2026-07-05T11:26:57Z"},{"alias_kind":"pith_short_12","alias_value":"XQLYIPHRBKAC","created_at":"2026-07-05T11:26:57Z"},{"alias_kind":"pith_short_16","alias_value":"XQLYIPHRBKACDRZP","created_at":"2026-07-05T11:26:57Z"},{"alias_kind":"pith_short_8","alias_value":"XQLYIPHR","created_at":"2026-07-05T11:26:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:XQLYIPHRBKACDRZPJQSXHIT3U2","target":"record","payload":{"canonical_record":{"source":{"id":"2506.19973","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2025-06-24T19:40:39Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"3bbda363df06fb043d4e5cf0fc448e56ed3f797dbfcad6fb180edb15e679d166","abstract_canon_sha256":"76ef1d934d277a9f65c140934a860f056b1f2c3f86561641a99656817350f434"},"schema_version":"1.0"},"canonical_sha256":"bc17843cf10a8021c72f4c2573a27ba6b992dac2b2e576587827f61161059330","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:26:57.473608Z","signature_b64":"jUwHPWjLgaxOrFZYXnf6kxlw4Ns/RT/b9RvfPPs4lePRqlZCUZMu32jWGnscrRO9qTpu7Kvn88G3pkziXiF/DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bc17843cf10a8021c72f4c2573a27ba6b992dac2b2e576587827f61161059330","last_reissued_at":"2026-07-05T11:26:57.473083Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:26:57.473083Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.19973","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:26:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XHxdcgAWA9ruNaRkPwGK5KFzPzX/aUpk5mDtb/5+AsXOge2y1G8dD6mAFFNDdWPpBwv2TVOARxda3XV9uKsrDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-25T05:21:48.109992Z"},"content_sha256":"24511b36c8ce8568be853669e0c8d625200c1b51cda4f2a903bdd2d4f3db5c7e","schema_version":"1.0","event_id":"sha256:24511b36c8ce8568be853669e0c8d625200c1b51cda4f2a903bdd2d4f3db5c7e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:XQLYIPHRBKACDRZPJQSXHIT3U2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Quantum Neural Networks for Propensity Score Estimation and Survival Analysis in Observational Biomedical Studies","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","stat.ML"],"primary_cat":"quant-ph","authors_text":"Ivan Zelinka, Lenka P\\v{r}ibylov\\'a, Lubom\\'ir Mart\\'inek, Vojt\\v{e}ch Nov\\'ak","submitted_at":"2025-06-24T19:40:39Z","abstract_excerpt":"This study investigates the application of quantum neural networks (QNNs) for propensity score estimation to address selection bias in comparing survival outcomes between laparoscopic and open surgical techniques in a cohort of 1177 colorectal carcinoma patients treated at University Hospital Ostrava (2001-2009). Using a dataset with 77 variables, including patient demographics and tumor characteristics, we developed QNN-based propensity score models focusing on four key covariates (Age, Sex, Stage, BMI). The QNN architecture employed a linear ZFeatureMap for data encoding, a SummedPaulis oper"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.19973","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/2506.19973/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:26:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3FSnzTvpTrsYjtGjU6QgqNAEwMEbcBSOj0jdgMnVfOB4hdi+lhgk+vwaJEMTjutYbJiHe84LjO+9uDf35qdVBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-25T05:21:48.110390Z"},"content_sha256":"456ecef4798cf51842cd8a15e75e62c0ea79097b99b0d88a3b0dcf7362e8e6de","schema_version":"1.0","event_id":"sha256:456ecef4798cf51842cd8a15e75e62c0ea79097b99b0d88a3b0dcf7362e8e6de"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XQLYIPHRBKACDRZPJQSXHIT3U2/bundle.json","state_url":"https://pith.science/pith/XQLYIPHRBKACDRZPJQSXHIT3U2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XQLYIPHRBKACDRZPJQSXHIT3U2/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-25T05:21:48Z","links":{"resolver":"https://pith.science/pith/XQLYIPHRBKACDRZPJQSXHIT3U2","bundle":"https://pith.science/pith/XQLYIPHRBKACDRZPJQSXHIT3U2/bundle.json","state":"https://pith.science/pith/XQLYIPHRBKACDRZPJQSXHIT3U2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XQLYIPHRBKACDRZPJQSXHIT3U2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:XQLYIPHRBKACDRZPJQSXHIT3U2","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":"76ef1d934d277a9f65c140934a860f056b1f2c3f86561641a99656817350f434","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2025-06-24T19:40:39Z","title_canon_sha256":"3bbda363df06fb043d4e5cf0fc448e56ed3f797dbfcad6fb180edb15e679d166"},"schema_version":"1.0","source":{"id":"2506.19973","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.19973","created_at":"2026-07-05T11:26:57Z"},{"alias_kind":"arxiv_version","alias_value":"2506.19973v1","created_at":"2026-07-05T11:26:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.19973","created_at":"2026-07-05T11:26:57Z"},{"alias_kind":"pith_short_12","alias_value":"XQLYIPHRBKAC","created_at":"2026-07-05T11:26:57Z"},{"alias_kind":"pith_short_16","alias_value":"XQLYIPHRBKACDRZP","created_at":"2026-07-05T11:26:57Z"},{"alias_kind":"pith_short_8","alias_value":"XQLYIPHR","created_at":"2026-07-05T11:26:57Z"}],"graph_snapshots":[{"event_id":"sha256:456ecef4798cf51842cd8a15e75e62c0ea79097b99b0d88a3b0dcf7362e8e6de","target":"graph","created_at":"2026-07-05T11:26:57Z","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/2506.19973/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This study investigates the application of quantum neural networks (QNNs) for propensity score estimation to address selection bias in comparing survival outcomes between laparoscopic and open surgical techniques in a cohort of 1177 colorectal carcinoma patients treated at University Hospital Ostrava (2001-2009). Using a dataset with 77 variables, including patient demographics and tumor characteristics, we developed QNN-based propensity score models focusing on four key covariates (Age, Sex, Stage, BMI). The QNN architecture employed a linear ZFeatureMap for data encoding, a SummedPaulis oper","authors_text":"Ivan Zelinka, Lenka P\\v{r}ibylov\\'a, Lubom\\'ir Mart\\'inek, Vojt\\v{e}ch Nov\\'ak","cross_cats":["cs.AI","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2025-06-24T19:40:39Z","title":"Quantum Neural Networks for Propensity Score Estimation and Survival Analysis in Observational Biomedical Studies"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.19973","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":"sha256:24511b36c8ce8568be853669e0c8d625200c1b51cda4f2a903bdd2d4f3db5c7e","target":"record","created_at":"2026-07-05T11:26:57Z","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":"76ef1d934d277a9f65c140934a860f056b1f2c3f86561641a99656817350f434","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2025-06-24T19:40:39Z","title_canon_sha256":"3bbda363df06fb043d4e5cf0fc448e56ed3f797dbfcad6fb180edb15e679d166"},"schema_version":"1.0","source":{"id":"2506.19973","kind":"arxiv","version":1}},"canonical_sha256":"bc17843cf10a8021c72f4c2573a27ba6b992dac2b2e576587827f61161059330","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bc17843cf10a8021c72f4c2573a27ba6b992dac2b2e576587827f61161059330","first_computed_at":"2026-07-05T11:26:57.473083Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:26:57.473083Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"jUwHPWjLgaxOrFZYXnf6kxlw4Ns/RT/b9RvfPPs4lePRqlZCUZMu32jWGnscrRO9qTpu7Kvn88G3pkziXiF/DA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:26:57.473608Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.19973","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:24511b36c8ce8568be853669e0c8d625200c1b51cda4f2a903bdd2d4f3db5c7e","sha256:456ecef4798cf51842cd8a15e75e62c0ea79097b99b0d88a3b0dcf7362e8e6de"],"state_sha256":"7d7b6c5af842583c8166d93fd3d333742dfaacb4ca9c715c937de442a0c3ea3e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rSI5aSFTvJbHqpa0cKDbHVWX5mvISlwmLx5Jht6nZtO8K6hCWl7643z5h9TrgywjPtOzXSVZbraV65IMDUA7BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-25T05:21:48.113114Z","bundle_sha256":"684e6d1026b1856fafb7c1960e2413dd0e54c968a7c27bbc2cb5ccd78ab337eb"}}