{"id":"W3112017177","doi":"10.1002/alz.043492","title":"Predicting progression in subjective cognitive decline (SCD) using a machine learning (ML) approach: The role of the complaint’s severity","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Complaint; Cognition; Medicine; Random forest; Confusion; Sensibility; Internal medicine; Clinical psychology; Psychology; Machine learning; Psychiatry","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":[0.005913184,0.0007460898,0.0007789871,0.002866207,0.0002552927,0.001367722,0.0005655274,0.0007427053,0.0007923699],"category_scores_gemma":[0.01285803,0.000191594,0.000853717,0.0007987444,0.0002554858,0.0006801854,0.0004832316,0.0007647597,0.0003205488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004064034,"about_ca_system_score_gemma":0.0004667433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003188101,"about_ca_topic_score_gemma":0.002956616,"domain_scores_codex":[0.9984275,0.0009742163,0.0001346445,0.0001998387,0.0001715985,0.00009222546],"domain_scores_gemma":[0.9897737,0.007189814,0.001155692,0.0003705214,0.001113316,0.0003969695],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008556614,0.0003037549,0.9299809,0.00006877458,0.000245446,0.00004510596,0.00007462449,0.01118703,0.000675093,0.00008830326,0.0004599618,0.05601529],"study_design_scores_gemma":[0.00008104136,0.001346219,0.4862253,0.0001307552,0.0002623445,0.000331369,0.0002470984,0.508121,0.001400081,0.001421887,0.0003744225,0.00005862574],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9790134,0.0007840524,0.0185575,0.0002883062,0.00004029781,0.00006332171,0.0004403022,0.0002044492,0.0006084437],"genre_scores_gemma":[0.9936523,0.00007597539,0.005893576,0.00003168437,0.0000279318,0.00002111282,0.0002080467,0.000004311838,0.00008487696],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005913184,"threshold_uncertainty_score":0.03127229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0400470060835298,"score_gpt":0.317409942154199,"score_spread":0.2773629360706692,"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."}}