{"id":"W2970186575","doi":"10.1016/s2589-7500(19)30105-0","title":"Development and validation of the automated imaging differentiation in parkinsonism (AID-P): a multicentre machine learning study","year":2019,"lang":"en","type":"article","venue":"The Lancet Digital Health","topic":"Parkinson's Disease Mechanisms and Treatments","field":"Medicine","cited_by":117,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Environmental Health Sciences; National Institute of Neurological Disorders and Stroke; Parkinsonfonden; National Institutes of Health; Merz Pharmaceuticals; Eisai; Austrian Science Fund; Multiple System Atrophy Coalition; AOP Orphan; Parkinson Alliance; ACADIA Pharmaceuticals; Jazz Pharmaceuticals; H. Lundbeck A/S; Sunovion; Acorda Therapeutics; Takeda Pharmaceuticals U.S.A.; Neurocrine Biosciences; Vanderbilt University; Dystonia Medical Research Foundation; University of Florida Foundation; AbbVie; Teva Pharmaceutical Industries; Allergan; International Parkinson and Movement Disorder Society; National Parkinson Foundation; Pfizer; Biogen; Mutualité Sociale Agricole; U.S. Department of Defense; Sanofi; Parkinson's Foundation; Michael J. Fox Foundation for Parkinson's Research; Roche; U.S. Department of Veterans Affairs; Medtronic","keywords":"Parkinsonism; Diffusion MRI; Medicine; Neuroscience; Medical physics; Physical medicine and rehabilitation; Computer science; Magnetic resonance imaging; Pathology; Psychology; Radiology; Disease","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002193667,0.00009638825,0.0002403694,0.00003962302,0.00007995449,0.00002979411,0.00005680386,0.00001288408,0.000006260017],"category_scores_gemma":[0.00002798879,0.00005372627,0.00002108596,0.0001106548,0.00001178555,0.00008448367,0.00005676402,0.000101837,0.000007163782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008460076,"about_ca_system_score_gemma":0.00007898334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009853415,"about_ca_topic_score_gemma":0.00004738995,"domain_scores_codex":[0.9991659,0.00008164622,0.0002141581,0.0001542661,0.0001974276,0.0001866117],"domain_scores_gemma":[0.9995805,0.00004073148,0.0001464444,0.0001665003,0.00001791934,0.00004789102],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001156746,0.0003593442,0.9790509,0.00009045427,0.00003246982,0.00000254266,0.002863831,0.0000213036,0.00004158146,0.00002021279,0.000005876003,0.01739582],"study_design_scores_gemma":[0.003759887,0.00007995849,0.9824376,0.0001577094,0.00001714001,0.000004742791,0.0007582689,0.01159048,0.0003220238,0.00003684447,0.0007843621,0.0000509517],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980315,0.0002006245,0.00001211423,0.0005764752,0.00005402714,0.0009017215,0.00001156228,0.00005962417,0.0001523356],"genre_scores_gemma":[0.9995869,0.0000206339,0.00009183575,0.0001314836,0.00001335178,0.00001464853,0.0000522837,0.00001040222,0.00007849636],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01734487,"threshold_uncertainty_score":0.2190894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02105458024454335,"score_gpt":0.2946326005273567,"score_spread":0.2735780202828134,"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."}}