{"id":"W2034298182","doi":"10.1016/j.jalz.2010.05.146","title":"IC‐P‐131: Robust Identification of Amnestic MCI Progressors to Probable Alzheimer's disease Via Baseline MRI Analysis","year":2010,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Medicine; Neuroimaging; Linear discriminant analysis; Nuclear medicine; Robustness (evolution); Alzheimer's Disease Neuroimaging Initiative; Missing data; Artificial intelligence; Psychology; Pattern recognition (psychology); Computer science; Internal medicine; Statistics; Disease; Mathematics; Alzheimer's disease; Neuroscience","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":[0.002134502,0.0009384579,0.0010434,0.001730787,0.0003466903,0.0009344946,0.0009805667,0.0007982228,0.002062189],"category_scores_gemma":[0.005357385,0.0003036101,0.0005380972,0.0004648932,0.000340781,0.0004416361,0.0009882856,0.0006150526,0.00122107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002902762,"about_ca_system_score_gemma":0.0005995341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003817284,"about_ca_topic_score_gemma":0.00685097,"domain_scores_codex":[0.9992803,0.0001373938,0.00004861851,0.0003145302,0.000137074,0.00008209873],"domain_scores_gemma":[0.9987227,0.0003352682,0.0001690089,0.0003029472,0.0002697047,0.0002003616],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.01024715,0.001034883,0.3734156,0.0004195,0.001385336,0.001375116,0.0004056127,0.01819273,0.08660179,0.0006083199,0.01538501,0.4909289],"study_design_scores_gemma":[0.0003862815,0.00235084,0.7220114,0.00005869009,0.0005750307,0.003763854,0.0002150099,0.236784,0.02739032,0.001867968,0.004418327,0.00017831],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9589291,0.0006677993,0.03181253,0.0001117555,0.00004983771,0.0003098526,0.003439105,0.002668725,0.00201128],"genre_scores_gemma":[0.9613947,0.0001762124,0.02848284,0.00007923192,0.00006970289,0.00020097,0.007929748,0.0001888571,0.001477895],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003817284,"threshold_uncertainty_score":0.01128846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03538439306062507,"score_gpt":0.2822894896907511,"score_spread":0.2469050966301261,"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."}}