{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:W6J4GDV2D6NWOLGIRWIO63CZZP","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":"50ff1ecbed45cbcd7581e6f31196d590da96fe37653789f4ea435c5074c438b0","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-28T15:18:16Z","title_canon_sha256":"7aff1fa155e3bda304894fa6b4834a02a3fcedbecca04582545c3f3b747083a6"},"schema_version":"1.0","source":{"id":"2505.22465","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.22465","created_at":"2026-07-05T11:12:34Z"},{"alias_kind":"arxiv_version","alias_value":"2505.22465v2","created_at":"2026-07-05T11:12:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.22465","created_at":"2026-07-05T11:12:34Z"},{"alias_kind":"pith_short_12","alias_value":"W6J4GDV2D6NW","created_at":"2026-07-05T11:12:34Z"},{"alias_kind":"pith_short_16","alias_value":"W6J4GDV2D6NWOLGI","created_at":"2026-07-05T11:12:34Z"},{"alias_kind":"pith_short_8","alias_value":"W6J4GDV2","created_at":"2026-07-05T11:12:34Z"}],"graph_snapshots":[{"event_id":"sha256:524f7373cf2037f022a74ba209972883bef90dfcc85c8758d8bb87be82a6b887","target":"graph","created_at":"2026-07-05T11:12:34Z","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/2505.22465/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Although Alzheimer's disease detection via MRIs has advanced significantly thanks to contemporary deep learning models, challenges such as class imbalance, protocol variations, and limited dataset diversity often hinder their generalization capacity. To address this issue, this article focuses on the single domain generalization setting, where given the data of one domain, a model is designed and developed with maximal performance w.r.t. an unseen domain of distinct distribution. Since brain morphology is known to play a crucial role in Alzheimer's diagnosis, we propose the use of learnable ps","authors_text":"Erchan Aptoula, Huseyin Ozkan, Zobia Batool","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-28T15:18:16Z","title":"Single Domain Generalization for Alzheimer's Detection from 3D MRIs with Pseudo-Morphological Augmentations and Contrastive Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.22465","kind":"arxiv","version":2},"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:c0f8c0e3b0d10c9f3a9cae8e814ef5bb3fb344037322bbeea7ab2f4f8098fa88","target":"record","created_at":"2026-07-05T11:12:34Z","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":"50ff1ecbed45cbcd7581e6f31196d590da96fe37653789f4ea435c5074c438b0","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-28T15:18:16Z","title_canon_sha256":"7aff1fa155e3bda304894fa6b4834a02a3fcedbecca04582545c3f3b747083a6"},"schema_version":"1.0","source":{"id":"2505.22465","kind":"arxiv","version":2}},"canonical_sha256":"b793c30eba1f9b672cc88d90ef6c59cbea0ea35b5940ffbb34549a0169e1c4a5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b793c30eba1f9b672cc88d90ef6c59cbea0ea35b5940ffbb34549a0169e1c4a5","first_computed_at":"2026-07-05T11:12:34.192600Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:12:34.192600Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XCOmCO0hAgnAYYPkKqiT1nQQyi5T0YT89BICsGDBco+dACeQ9acA1WtTEJ/4Hh8Lk7o5CFB4oNPjIc8RKSBqCA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:12:34.193143Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.22465","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c0f8c0e3b0d10c9f3a9cae8e814ef5bb3fb344037322bbeea7ab2f4f8098fa88","sha256:524f7373cf2037f022a74ba209972883bef90dfcc85c8758d8bb87be82a6b887"],"state_sha256":"0f84ee7dced99f3ac9db1452bf20c0195e768d386d4387feaac5eed8d0302b6e"}