{"id":"W4414192602","doi":"10.1088/1361-6579/ae06ed","title":"Cognitive impairment assessment using eye-tracking: multilevel saccade paradigms with differential analysis and attention-based neural networks","year":2025,"lang":"en","type":"article","venue":"Physiological Measurement","topic":"Cognitive Science and Mapping","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; National Key Research and Development Program of China","keywords":"Saccade; Eye movement; Cognition; Set (abstract data type); Artificial neural network; Receiver operating characteristic; Feature selection","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000545366,0.0005202856,0.0004670112,0.0009363555,0.0001511118,0.0004042267,0.0004451514,0.0003712238,0.0006524532],"category_scores_gemma":[0.001072756,0.0001387397,0.00064884,0.0005599255,0.0001585354,0.0003046391,0.0006282775,0.0003719977,0.0001208077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004681979,"about_ca_system_score_gemma":0.0003696828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004202663,"about_ca_topic_score_gemma":0.007161171,"domain_scores_codex":[0.9997407,0.00007090507,0.00001716592,0.00008422802,0.0000601667,0.00002687705],"domain_scores_gemma":[0.9997144,0.0001056615,0.00005319604,0.00002770304,0.00007704459,0.00002202932],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001868217,0.001104015,0.03092609,0.0004073317,0.0005882219,0.0002608323,0.000136484,0.07070581,0.2224202,0.001471987,0.002193925,0.667917],"study_design_scores_gemma":[0.00006071405,0.0006571272,0.04536368,0.00002933572,0.0001455406,0.0001459281,0.00002858516,0.9279402,0.02354519,0.001327913,0.0007208154,0.00003499296],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7034856,0.001154505,0.2912033,0.0001861719,0.00007508845,0.000325271,0.0005314699,0.0006751921,0.002363302],"genre_scores_gemma":[0.9094376,0.0002269866,0.08861253,0.0000757793,0.00002973007,0.0001831848,0.0003390967,0.00002000163,0.001075009],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004202663,"threshold_uncertainty_score":0.008356392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07771350536375494,"score_gpt":0.3353851128102681,"score_spread":0.2576716074465131,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}