{"id":"W3200973239","doi":"10.3389/fnhum.2021.716670","title":"Classification of Alzheimer’s Disease Leveraging Multi-task Machine Learning Analysis of Speech and Eye-Movement Data","year":2021,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Alzheimer’s Society; Vancouver Coastal Health Research Institute; Alzheimer's Society; Centre for Aging + Brain Health Innovation; Consortium canadien en neurodégénérescence associée au vieillissement","keywords":"Discriminative model; Eye movement; Cognition; Task (project management); Computer science; Paragraph; Memory clinic; Cognitive impairment; Psychology; Cognitive psychology; Artificial intelligence; Neuroscience","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004963739,0.00008680274,0.0002692689,0.000462255,0.00008326393,0.00002269627,0.000194382,0.00001687468,0.00002788668],"category_scores_gemma":[0.0003276747,0.00008486732,0.00004686029,0.00102343,0.0002580022,0.0001517788,0.0002785744,0.0001509997,8.963221e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002080295,"about_ca_system_score_gemma":0.00008542266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003886118,"about_ca_topic_score_gemma":0.00001289196,"domain_scores_codex":[0.9984211,0.0001238118,0.0002973753,0.0004950069,0.0004740756,0.0001886768],"domain_scores_gemma":[0.9992,0.00001733697,0.0001236287,0.0004397162,0.0001048731,0.0001144213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002506567,0.0002225625,0.8902053,0.0000447939,0.00005738342,0.00004935801,0.00009669185,0.00009557162,0.1044561,0.00001360228,0.00003780042,0.004695734],"study_design_scores_gemma":[0.0004913984,0.00005651791,0.7740119,0.00003454109,0.0004441339,4.881954e-7,0.0001994415,0.2201515,0.00441511,0.00001448821,0.0001288845,0.0000516382],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9791357,0.001059882,0.01905817,0.0002483034,0.00009207299,0.0002253049,0.00004644641,0.000009364159,0.0001247584],"genre_scores_gemma":[0.9974976,0.000214848,0.001642224,0.0001117301,0.000007684645,0.000005396067,0.0001523103,0.0000063868,0.0003618735],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.220056,"threshold_uncertainty_score":0.3460789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09003650604075948,"score_gpt":0.3720424939299207,"score_spread":0.2820059878891613,"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."}}