{"id":"W3005163827","doi":"10.59275/j.melba.2021-2dcc","title":"The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up","year":2021,"lang":"en","type":"article","venue":"The Journal of Machine Learning for Biomedical Imaging","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"EPSRC Centre for Doctoral Training in Medical Imaging; National Institutes of Health; Medical Research Council; Medical Delta; Direktoratet for internasjonalisering og kvalitetsutvikling i høgare utdanning; National Research Foundation Singapore; National Institute of Neurological Disorders and Stroke; National Institute for Health and Care Research; Alzheimer's Society; European Federation of Pharmaceutical Industries and Associations; National Research Foundation; Engineering and Physical Sciences Research Council; UK Research and Innovation; National Institute on Aging; Alzheimer's Association; National Institute of Biomedical Imaging and Bioengineering; Portland State University; University College London Hospitals NHS Foundation Trust; U.S. Department of Defense; European Commission; Alzheimer's Disease Neuroimaging Initiative; National Science Foundation","keywords":"Disease; Machine learning; Multivariate statistics; Artificial intelligence; Support vector machine; Medicine; Computer science; Physical medicine and rehabilitation; Internal medicine","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":[0.005955705,0.001770769,0.001620136,0.0005428192,0.0004899739,0.0008557995,0.000971101,0.001639477,0.001112443],"category_scores_gemma":[0.01216657,0.0002244829,0.001665037,0.0002743006,0.0002464231,0.0008469521,0.001425743,0.001413757,0.001004034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004488447,"about_ca_system_score_gemma":0.000721162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00750702,"about_ca_topic_score_gemma":0.007229768,"domain_scores_codex":[0.9986296,0.0005480396,0.00009992485,0.0003881001,0.0002037763,0.0001306823],"domain_scores_gemma":[0.9937235,0.002229839,0.0004184929,0.0009658681,0.001651425,0.001010844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.03492322,0.009886133,0.3880143,0.001389799,0.006670491,0.001171145,0.0008951451,0.08000186,0.007664514,0.0005640406,0.1218063,0.347013],"study_design_scores_gemma":[0.003293595,0.03039885,0.541567,0.0006133752,0.003068974,0.001998589,0.001318369,0.3680665,0.01330773,0.003195796,0.03261497,0.0005562791],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9689836,0.002608731,0.004671975,0.0007883277,0.0004247004,0.0004096094,0.01910713,0.001111521,0.001894369],"genre_scores_gemma":[0.9327269,0.0005697641,0.01002365,0.0004069602,0.0002191737,0.000496373,0.05299493,0.000149207,0.002413197],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00750702,"threshold_uncertainty_score":0.03149718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01902432039102666,"score_gpt":0.3133916186062761,"score_spread":0.2943672982152494,"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."}}