{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:K3FITHKKJWYZF4G6TAYT5YMQD7","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":"f6ef95d2a15905d19fc578c2c20288cd3b938e0e8829c884868a5b96ef676ddf","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-09-22T02:02:59Z","title_canon_sha256":"d196f133096c679c9634834403a60c358ab16cee1a1db7b420d15f6a10e15366"},"schema_version":"1.0","source":{"id":"2309.12574","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.12574","created_at":"2026-07-05T06:53:14Z"},{"alias_kind":"arxiv_version","alias_value":"2309.12574v1","created_at":"2026-07-05T06:53:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.12574","created_at":"2026-07-05T06:53:14Z"},{"alias_kind":"pith_short_12","alias_value":"K3FITHKKJWYZ","created_at":"2026-07-05T06:53:14Z"},{"alias_kind":"pith_short_16","alias_value":"K3FITHKKJWYZF4G6","created_at":"2026-07-05T06:53:14Z"},{"alias_kind":"pith_short_8","alias_value":"K3FITHKK","created_at":"2026-07-05T06:53:14Z"}],"graph_snapshots":[{"event_id":"sha256:5d4afb5e3c90f7aa73f664ccc663acc723d3bd2d0a24da6146e512d3c498ef77","target":"graph","created_at":"2026-07-05T06:53:14Z","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/2309.12574/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Existing research has shown the potential of classifying Alzheimers Disease (AD) from eye-tracking (ET) data with classifiers that rely on task-specific engineered features. In this paper, we investigate whether we can improve on existing results by using a Deep-Learning classifier trained end-to-end on raw ET data. This classifier (VTNet) uses a GRU and a CNN in parallel to leverage both visual (V) and temporal (T) representations of ET data and was previously used to detect user confusion while processing visual displays. A main challenge in applying VTNet to our target AD classification tas","authors_text":"Cristina Conati, Harshinee Sriram, Thalia Field","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-09-22T02:02:59Z","title":"Classification of Alzheimers Disease with Deep Learning on Eye-tracking Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.12574","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":"sha256:2205a950aa9ccedae875c0c7829a28a8123d24a61cde9c0282e79189053a6814","target":"record","created_at":"2026-07-05T06:53:14Z","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":"f6ef95d2a15905d19fc578c2c20288cd3b938e0e8829c884868a5b96ef676ddf","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-09-22T02:02:59Z","title_canon_sha256":"d196f133096c679c9634834403a60c358ab16cee1a1db7b420d15f6a10e15366"},"schema_version":"1.0","source":{"id":"2309.12574","kind":"arxiv","version":1}},"canonical_sha256":"56ca899d4a4db192f0de98313ee1901ffab08a96b287c773eb554cfbf003d06e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"56ca899d4a4db192f0de98313ee1901ffab08a96b287c773eb554cfbf003d06e","first_computed_at":"2026-07-05T06:53:14.555563Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:53:14.555563Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1lfjL+LE1uB1huAQAcpUa8OIPMKc0N3BI5ll1+dYeU25lw4XaLJTYWDKxqGV48mDpnDiMPpVkeo/GVzYY0+KBA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:53:14.556035Z","signed_message":"canonical_sha256_bytes"},"source_id":"2309.12574","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2205a950aa9ccedae875c0c7829a28a8123d24a61cde9c0282e79189053a6814","sha256:5d4afb5e3c90f7aa73f664ccc663acc723d3bd2d0a24da6146e512d3c498ef77"],"state_sha256":"166f85e4f820ea4cc64636bdabbfbeaf91e9737d15580da978a7cd1cedac8211"}