{"id":"W4387031219","doi":"10.1145/3577190.3614149","title":"Classification of Alzheimer's Disease with Deep Learning on Eye-tracking Data","year":2023,"lang":"en","type":"article","venue":"INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Generality; Artificial intelligence; Leverage (statistics); Classifier (UML); Confusion; Machine learning; Deep learning; Eye tracking; Pattern recognition (psychology)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001035906,0.001024719,0.0005013236,0.001558695,0.0001830031,0.0006195921,0.0005385572,0.000776249,0.001217207],"category_scores_gemma":[0.003526189,0.0001789541,0.0005687455,0.0007330843,0.0001620114,0.0008772417,0.0006392407,0.0009524403,0.0007765057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000594517,"about_ca_system_score_gemma":0.0004284165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008350146,"about_ca_topic_score_gemma":0.01212423,"domain_scores_codex":[0.999651,0.00006805723,0.00003932754,0.0001181306,0.00005680389,0.00006671136],"domain_scores_gemma":[0.9986821,0.0005588355,0.0001550932,0.000166402,0.000359657,0.00007787837],"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":[0.001610689,0.001015461,0.1836785,0.0003206687,0.0004118033,0.0007504768,0.000203539,0.06449271,0.02264109,0.000777541,0.01527591,0.7088216],"study_design_scores_gemma":[0.00004746169,0.0003869856,0.04780304,0.0001010764,0.00007194297,0.0003405829,0.0001468166,0.9333192,0.01255632,0.00292884,0.002262294,0.00003541993],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9126668,0.003129686,0.07043028,0.0008318389,0.0002657366,0.0001467085,0.007209439,0.002217325,0.00310225],"genre_scores_gemma":[0.9624736,0.0005195818,0.02922614,0.0001899621,0.00008349356,0.00006549129,0.005260798,0.00003297987,0.002148023],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008350146,"threshold_uncertainty_score":0.01660305,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1378145303123562,"score_gpt":0.389955937920352,"score_spread":0.2521414076079957,"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."}}