{"id":"W2115457642","doi":"10.1016/j.jalz.2012.06.004","title":"Standardization of analysis sets for reporting results from ADNI MRI data","year":2012,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":237,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health; Alzheimer's Disease Neuroimaging Initiative; Bayer HealthCare; National Institute for Health and Care Research; Abbott Laboratories; BioClinica; Bristol-Myers Squibb; Eli Lilly and Company; AstraZeneca; Alzheimer's Drug Discovery Foundation; Amorfix Life Sciences; National Institute on Aging; Alzheimer's Association","keywords":"Standardization; Computer science; Data mining; Database; Operating system","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":[],"consensus_categories":[],"category_scores_codex":[0.0005671015,0.00008356384,0.0002554286,0.00006936325,0.00005969021,0.000005933299,0.0001140383,0.00004739515,0.00004875908],"category_scores_gemma":[0.0002013493,0.00007657589,0.00008618459,0.0002945179,0.00002394875,0.0001682413,0.00009231995,0.00004473855,0.000001972132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004137264,"about_ca_system_score_gemma":0.00002711429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009136017,"about_ca_topic_score_gemma":0.00001455275,"domain_scores_codex":[0.998607,0.00001063294,0.0007959335,0.0002577596,0.0001631198,0.0001655927],"domain_scores_gemma":[0.997896,0.00006150366,0.0008826107,0.000945247,0.0001422806,0.00007236264],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001121894,0.001381681,0.1007691,0.00003853466,0.07685395,0.000006033581,0.001580183,0.002469975,0.03420415,0.00379983,0.09590473,0.6818699],"study_design_scores_gemma":[0.001971619,0.0001385337,0.03304157,0.00006420175,0.2144167,0.000004285472,0.0002294527,0.0128295,0.2733958,0.001108693,0.4624188,0.0003808358],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002651135,0.009819829,0.9846331,0.0004020121,0.0000435236,0.0005184741,0.001338931,0.00006735542,0.0005255968],"genre_scores_gemma":[0.6439306,0.00006508297,0.3506177,0.00005168176,0.00007344289,0.00002789655,0.005218489,0.000010568,0.000004514605],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6814891,"threshold_uncertainty_score":0.3122674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1218105666799814,"score_gpt":0.4147237200775171,"score_spread":0.2929131533975357,"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."}}