{"id":"W7114917324","doi":"10.1016/j.dajour.2025.100667","title":"An adaptive learning framework for Alzheimer’s disease diagnosis using structural Magnetic Resonance Imaging data analytics","year":2025,"lang":"en","type":"article","venue":"Decision Analytics Journal","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Saskatchewan Polytechnic","funders":"","keywords":"Neuroimaging; Domain (mathematical analysis); Domain adaptation; Feature (linguistics); Class (philosophy); Adaptation (eye); Pattern recognition (psychology); Deep learning; Functional magnetic resonance imaging","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001192181,0.0002587775,0.0004190042,0.0006614,0.0006594743,0.000447297,0.0006143182,0.00007840629,0.0004486885],"category_scores_gemma":[0.002795062,0.0002206806,0.0002112803,0.0007805086,0.0001446738,0.0004430768,0.0002983905,0.000882999,0.000007426253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001521585,"about_ca_system_score_gemma":0.0006021885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008406605,"about_ca_topic_score_gemma":0.000004419819,"domain_scores_codex":[0.9971011,0.0001590559,0.0006402245,0.0005774651,0.0009380725,0.0005840369],"domain_scores_gemma":[0.996603,0.0008870765,0.0001988093,0.0007471791,0.0009278447,0.0006360748],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001599547,0.0001724046,0.5881197,0.00001664295,0.0001700208,0.0003331271,0.00003850173,0.0008746487,0.00003118498,0.0007319548,0.001565633,0.4063466],"study_design_scores_gemma":[0.001613227,0.000384387,0.2526692,0.0007598791,0.001672676,0.00006607044,0.000498389,0.7219426,0.00004808345,0.01550314,0.004641308,0.000201059],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2222233,0.01663104,0.7584099,0.001292204,0.0004368922,0.0006650851,0.0001132035,0.00004228754,0.0001860918],"genre_scores_gemma":[0.9175477,0.0008002933,0.08028555,0.000719474,0.0003511065,0.000008628263,0.00007385874,0.00003659953,0.0001768093],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.721068,"threshold_uncertainty_score":0.8999091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1036282463531432,"score_gpt":0.4385273532928715,"score_spread":0.3348991069397284,"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."}}