{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:6U4PPPFKPQAFXOB24MVESNUDCE","short_pith_number":"pith:6U4PPPFK","canonical_record":{"source":{"id":"2304.04077","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-04-08T17:43:31Z","cross_cats_sorted":[],"title_canon_sha256":"fa3b83fe08e9e5679aad445317c46e7a40238a723f9b3c7c090891a45c8975a5","abstract_canon_sha256":"80f29efbaaab83b3fd864772150067facecc6b33491123fb9a490ab8235f19e8"},"schema_version":"1.0"},"canonical_sha256":"f538f7bcaa7c005bb83ae32a49368311385aa728c46cd1a8c90eaeba1cf7b977","source":{"kind":"arxiv","id":"2304.04077","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.04077","created_at":"2026-07-05T05:59:10Z"},{"alias_kind":"arxiv_version","alias_value":"2304.04077v1","created_at":"2026-07-05T05:59:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.04077","created_at":"2026-07-05T05:59:10Z"},{"alias_kind":"pith_short_12","alias_value":"6U4PPPFKPQAF","created_at":"2026-07-05T05:59:10Z"},{"alias_kind":"pith_short_16","alias_value":"6U4PPPFKPQAFXOB2","created_at":"2026-07-05T05:59:10Z"},{"alias_kind":"pith_short_8","alias_value":"6U4PPPFK","created_at":"2026-07-05T05:59:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:6U4PPPFKPQAFXOB24MVESNUDCE","target":"record","payload":{"canonical_record":{"source":{"id":"2304.04077","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-04-08T17:43:31Z","cross_cats_sorted":[],"title_canon_sha256":"fa3b83fe08e9e5679aad445317c46e7a40238a723f9b3c7c090891a45c8975a5","abstract_canon_sha256":"80f29efbaaab83b3fd864772150067facecc6b33491123fb9a490ab8235f19e8"},"schema_version":"1.0"},"canonical_sha256":"f538f7bcaa7c005bb83ae32a49368311385aa728c46cd1a8c90eaeba1cf7b977","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:59:10.937619Z","signature_b64":"Rl5KUXXxEgrO8cSOhJRCltW5dxA9JIS2NSDTc2YHxjsruj9+iIqN9CeVNH4iRVbG2/r3bAMjNIpl8Z9q5kFnAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f538f7bcaa7c005bb83ae32a49368311385aa728c46cd1a8c90eaeba1cf7b977","last_reissued_at":"2026-07-05T05:59:10.937152Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:59:10.937152Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2304.04077","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":"2026-07-05T05:59:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mm9nK7UyTFumrTA7d/A6I/96DoA70v9aD895mfutNnTcw6RBfHGVh/xTpaCMOWHSd1lVbVl3I9qZLvINscfKCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-12T14:18:10.700894Z"},"content_sha256":"90d1507ad1cc9b3b6fc75ab682a4baec9fbcd5083d19a421ae6a5305a3535fc4","schema_version":"1.0","event_id":"sha256:90d1507ad1cc9b3b6fc75ab682a4baec9fbcd5083d19a421ae6a5305a3535fc4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:6U4PPPFKPQAFXOB24MVESNUDCE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep Prototypical-Parts Ease Morphological Kidney Stone Identification and are Competitively Robust to Photometric Perturbations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Christian Daul, Daniel Flores-Araiza, Francisco Lopez-Tiro, Gilberto Ochoa-Ruiz, Jacques Hubert, Jonathan El-Beze, Miguel Gonzalez-Mendoza","submitted_at":"2023-04-08T17:43:31Z","abstract_excerpt":"Identifying the type of kidney stones can allow urologists to determine their cause of formation, improving the prescription of appropriate treatments to diminish future relapses. Currently, the associated ex-vivo diagnosis (known as Morpho-constitutional Analysis, MCA) is time-consuming, expensive and requires a great deal of experience, as it requires a visual analysis component that is highly operator dependant. Recently, machine learning methods have been developed for in-vivo endoscopic stone recognition. Deep Learning (DL) based methods outperform non-DL methods in terms of accuracy but "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.04077","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/2304.04077/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":"2026-07-05T05:59:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bDH/d5f7wcRWRNWxDro9yiEc8PVnFXPH+D+mOnv59Jq7K5KwdTIWCwaRulTzxw1bQ0SrWuzCVGB/BQha/9gsAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-12T14:18:10.701266Z"},"content_sha256":"a951c4a52e9beeb3fb9d25e89f7303cc42763ec9bc4d829a1aced6aea2ba4076","schema_version":"1.0","event_id":"sha256:a951c4a52e9beeb3fb9d25e89f7303cc42763ec9bc4d829a1aced6aea2ba4076"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6U4PPPFKPQAFXOB24MVESNUDCE/bundle.json","state_url":"https://pith.science/pith/6U4PPPFKPQAFXOB24MVESNUDCE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6U4PPPFKPQAFXOB24MVESNUDCE/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":"2026-07-12T14:18:10Z","links":{"resolver":"https://pith.science/pith/6U4PPPFKPQAFXOB24MVESNUDCE","bundle":"https://pith.science/pith/6U4PPPFKPQAFXOB24MVESNUDCE/bundle.json","state":"https://pith.science/pith/6U4PPPFKPQAFXOB24MVESNUDCE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6U4PPPFKPQAFXOB24MVESNUDCE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:6U4PPPFKPQAFXOB24MVESNUDCE","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":"80f29efbaaab83b3fd864772150067facecc6b33491123fb9a490ab8235f19e8","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-04-08T17:43:31Z","title_canon_sha256":"fa3b83fe08e9e5679aad445317c46e7a40238a723f9b3c7c090891a45c8975a5"},"schema_version":"1.0","source":{"id":"2304.04077","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.04077","created_at":"2026-07-05T05:59:10Z"},{"alias_kind":"arxiv_version","alias_value":"2304.04077v1","created_at":"2026-07-05T05:59:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.04077","created_at":"2026-07-05T05:59:10Z"},{"alias_kind":"pith_short_12","alias_value":"6U4PPPFKPQAF","created_at":"2026-07-05T05:59:10Z"},{"alias_kind":"pith_short_16","alias_value":"6U4PPPFKPQAFXOB2","created_at":"2026-07-05T05:59:10Z"},{"alias_kind":"pith_short_8","alias_value":"6U4PPPFK","created_at":"2026-07-05T05:59:10Z"}],"graph_snapshots":[{"event_id":"sha256:a951c4a52e9beeb3fb9d25e89f7303cc42763ec9bc4d829a1aced6aea2ba4076","target":"graph","created_at":"2026-07-05T05:59:10Z","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/2304.04077/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Identifying the type of kidney stones can allow urologists to determine their cause of formation, improving the prescription of appropriate treatments to diminish future relapses. Currently, the associated ex-vivo diagnosis (known as Morpho-constitutional Analysis, MCA) is time-consuming, expensive and requires a great deal of experience, as it requires a visual analysis component that is highly operator dependant. Recently, machine learning methods have been developed for in-vivo endoscopic stone recognition. Deep Learning (DL) based methods outperform non-DL methods in terms of accuracy but ","authors_text":"Christian Daul, Daniel Flores-Araiza, Francisco Lopez-Tiro, Gilberto Ochoa-Ruiz, Jacques Hubert, Jonathan El-Beze, Miguel Gonzalez-Mendoza","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-04-08T17:43:31Z","title":"Deep Prototypical-Parts Ease Morphological Kidney Stone Identification and are Competitively Robust to Photometric Perturbations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.04077","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":"sha256:90d1507ad1cc9b3b6fc75ab682a4baec9fbcd5083d19a421ae6a5305a3535fc4","target":"record","created_at":"2026-07-05T05:59:10Z","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":"80f29efbaaab83b3fd864772150067facecc6b33491123fb9a490ab8235f19e8","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-04-08T17:43:31Z","title_canon_sha256":"fa3b83fe08e9e5679aad445317c46e7a40238a723f9b3c7c090891a45c8975a5"},"schema_version":"1.0","source":{"id":"2304.04077","kind":"arxiv","version":1}},"canonical_sha256":"f538f7bcaa7c005bb83ae32a49368311385aa728c46cd1a8c90eaeba1cf7b977","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f538f7bcaa7c005bb83ae32a49368311385aa728c46cd1a8c90eaeba1cf7b977","first_computed_at":"2026-07-05T05:59:10.937152Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:59:10.937152Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Rl5KUXXxEgrO8cSOhJRCltW5dxA9JIS2NSDTc2YHxjsruj9+iIqN9CeVNH4iRVbG2/r3bAMjNIpl8Z9q5kFnAw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:59:10.937619Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.04077","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:90d1507ad1cc9b3b6fc75ab682a4baec9fbcd5083d19a421ae6a5305a3535fc4","sha256:a951c4a52e9beeb3fb9d25e89f7303cc42763ec9bc4d829a1aced6aea2ba4076"],"state_sha256":"9c410032c89dc9429930628005d19eabb2a4e56813c90b865977f7944c157a69"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pa/mUpQstHaLJwEu6OKmjO+jo0upVCrc6QaDfIzKQaTq3mCuSWdnIrA0Mf8woZDQsmKvOH2uun59dgV/UIjPDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-12T14:18:10.703675Z","bundle_sha256":"88e62989faad9f5269ea3f7aaf155d5f174ae5c0d363dd176a39e473ef76af61"}}