{"id":"W2892049953","doi":"10.1002/jmri.26197","title":"The Canadian Dementia Imaging Protocol: Harmonizing National Cohorts","year":2018,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":145,"is_retracted":false,"has_abstract":true,"ca_institutions":"Baycrest Hospital; Sunnybrook Health Science Centre; Université de Sherbrooke; Western University; University of Toronto; Toronto Metropolitan University; Montreal Neurological Institute and Hospital; Université de Montréal; Institut Universitaire en Santé Mentale de Québec; Université Laval; University of Calgary; McGill University","funders":"National Institutes of Health; Fonds de Recherche du Québec - Santé; Alzheimer's Society","keywords":"Nuclear medicine; Medicine; Imaging phantom; Dementia; Fluid-attenuated inversion recovery; Protocol (science); Psychology; Magnetic resonance imaging; Radiology; Pathology; Disease","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.06340384,0.001807271,0.002102107,0.007700987,0.008139643,0.003932941,0.009877258,0.002778378,0.01645967],"category_scores_gemma":[0.05712007,0.001711515,0.00295852,0.01004625,0.002226096,0.001740895,0.003574097,0.00305416,0.007758818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03563543,"about_ca_system_score_gemma":0.124478,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6251654,"about_ca_topic_score_gemma":0.7341036,"domain_scores_codex":[0.9726971,0.01101755,0.004118311,0.001849533,0.008065025,0.002252419],"domain_scores_gemma":[0.8912756,0.005395857,0.004532778,0.01193994,0.0825804,0.004275269],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.01019393,0.001439108,0.05116605,0.004549144,0.0008380329,0.0009212483,0.003216834,0.004228828,0.00339096,0.01835917,0.7568865,0.1448102],"study_design_scores_gemma":[0.003391322,0.0009067463,0.2714829,0.00359853,0.0004447729,0.0006729455,0.001001957,0.001766063,0.001850377,0.003146385,0.7112724,0.0004657114],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"protocol","genre_gemma":"methods","genre_scores_codex":[0.04253644,0.004999521,0.09220705,0.008373244,0.003428585,0.4887431,0.232818,0.002777445,0.1241167],"genre_scores_gemma":[0.05222412,0.004490013,0.2197809,0.005077425,0.0005995871,0.4678137,0.2194838,0.001002344,0.02952807],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.3748346,"threshold_uncertainty_score":0.7540841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02357255273896645,"score_gpt":0.3248646477883946,"score_spread":0.3012920950494282,"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."}}