{"id":"W4223941278","doi":"10.21203/rs.3.rs-1550479/v1","title":"A robust framework to investigate the reliability and stability of explainable artificial intelligence markers of Mild Cognitive Impairment and Alzheimer’s Disease","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Regione Puglia; F. Hoffmann-La Roche; Biogen; BioClinica; European Regional Development Fund; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Neuropsychology; Dementia; Neurocognitive; Disease; Cognition; Reliability (semiconductor); Psychology; Multivariate statistics; Cognitive impairment; Multivariate analysis; Alzheimer's disease; Neuropsychological test; Clinical psychology; Cognitive psychology; Medicine; Machine learning; Computer science; Psychiatry; Internal medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0126618,0.001129677,0.001063744,0.00350364,0.0004752847,0.001781276,0.00130782,0.001361563,0.001027932],"category_scores_gemma":[0.03934818,0.0005012359,0.001337085,0.001184942,0.002829061,0.001373047,0.002073774,0.001439819,0.0001390751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001073539,"about_ca_system_score_gemma":0.0009805014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003734166,"about_ca_topic_score_gemma":0.001446447,"domain_scores_codex":[0.9957756,0.00253097,0.0001646652,0.0008340841,0.0004511565,0.0002434236],"domain_scores_gemma":[0.9680164,0.02340908,0.003864449,0.002957248,0.001261188,0.0004916431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004491002,0.0003341706,0.05709188,0.0001277313,0.001169253,0.0004515093,0.0003975212,0.7740672,0.006738462,0.108023,0.0008214687,0.05032868],"study_design_scores_gemma":[0.000008325334,0.00009778562,0.008764218,0.00001123093,0.00003025463,0.00003737673,0.0000263877,0.9532005,0.0004380961,0.03720603,0.0001580592,0.00002170173],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2247902,0.0004376222,0.7724589,0.0004527107,0.00003071579,0.00006829632,0.0004015283,0.0002100976,0.001150037],"genre_scores_gemma":[0.9573772,0.0001134245,0.04157445,0.00006470929,0.00006144633,0.00008122969,0.0003237171,0.00002960282,0.0003742173],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0126618,"threshold_uncertainty_score":0.06696278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1402864250704882,"score_gpt":0.4099339368302704,"score_spread":0.2696475117597822,"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."}}