{"id":"W4402577460","doi":"10.3390/app14188287","title":"Alzheimer’s Multiclassification Using Explainable AI Techniques","year":2024,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute for Information and Communications Technology Promotion; Canadian Institutes of Health Research; National Institutes of Health; H. Lundbeck A/S; Servier; Iran Telecommunication Research Center; Eisai; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; Ministry of Science and ICT, South Korea; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association","keywords":"Psychology","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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001172488,0.0001695548,0.0001364317,0.0003251953,0.0006240259,0.001263287,0.001361638,0.00007403782,0.00002861135],"category_scores_gemma":[0.00003190364,0.0001466487,0.00005063457,0.001951369,0.0003761619,0.001617572,0.000240213,0.0001645504,0.000301563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000791145,"about_ca_system_score_gemma":0.0002552917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001362131,"about_ca_topic_score_gemma":0.00001250214,"domain_scores_codex":[0.9978935,0.00003881457,0.0002947966,0.000782445,0.0004887269,0.0005017312],"domain_scores_gemma":[0.9991618,0.0001628141,0.0000567425,0.0004533568,0.00007185688,0.00009340131],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000001118617,0.00002529531,0.00001592346,0.00001103092,0.000008772464,0.00001116303,0.0009014381,0.0004128763,0.1005313,0.8130714,0.0006325591,0.08437716],"study_design_scores_gemma":[0.00001285694,0.00003626192,0.000009632597,0.00002963273,0.00000897185,0.00001319764,0.0004742726,0.4144246,0.5262929,0.04534183,0.01313319,0.0002226885],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009422526,0.0008636375,0.9596003,0.002469133,0.0005393143,0.0004346355,9.656438e-7,0.001285843,0.02538365],"genre_scores_gemma":[0.8748081,0.00001627767,0.1244755,0.0004344579,0.0000981343,0.00006718733,6.144429e-7,0.00001007038,0.00008972224],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8653855,"threshold_uncertainty_score":0.9997735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1153169236479364,"score_gpt":0.3621408146121811,"score_spread":0.2468238909642446,"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."}}