{"id":"W2782660935","doi":"10.1038/s41467-018-05892-0","title":"Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference","year":2018,"lang":"en","type":"article","venue":"Nature Communications","topic":"Amyotrophic Lateral Sclerosis Research","field":"Medicine","cited_by":586,"is_retracted":false,"has_abstract":true,"ca_institutions":"Parkwood Institute; St Joseph's Health Care; McGill University; University of British Columbia; Toronto Western Hospital; Sunnybrook Health Science Centre; Jewish General Hospital; Baycrest Hospital; University of Toronto; Western University; Université Laval; Occupational Cancer Research Centre; Health Sciences Centre; University Health Network","funders":"EPSRC Centre for Doctoral Training in Medical Imaging; Economic and Social Research Council; Engineering and Physical Sciences Research Council; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; Associazione Italiana Ricerca Alzheimer; IXICO; H. Lundbeck A/S; Servier; University College London Hospitals NHS Foundation Trust; Eisai; Wolfson Foundation; Brain Research Trust; Weston Brain Institute; National Institute on Aging; National Institute for Health and Care Research; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; Alzheimer's Society; Wellcome Trust; University of Southern California; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; National Institutes of Health; Rosetrees Trust; European Commission; Alzheimer's Disease Neuroimaging Initiative; Medical Research Council; Meso Scale Diagnostics; Alzheimer's Association; Michael J. Fox Foundation for Parkinson's Research; Foundation for the National Institutes of Health","keywords":"Neurodegeneration; Disease; Inference; Frontotemporal dementia; Precision medicine; Phenotype; Biology; Genetic heterogeneity; Neuroscience; Computational biology; Dementia; Biomarker discovery; Bioinformatics; Medicine; Computer science; Genetics; Artificial intelligence; Pathology; Gene","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009131701,0.00007283472,0.0001275989,0.00002607332,0.0002494052,0.00002120871,0.0002257297,0.000052627,0.000008817012],"category_scores_gemma":[0.0001612912,0.00004137528,0.00001395251,0.0001565299,0.001635914,0.00006540091,0.0003763268,0.0003896186,7.147688e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001564834,"about_ca_system_score_gemma":0.00007176078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002084992,"about_ca_topic_score_gemma":0.002817699,"domain_scores_codex":[0.999405,0.0001272066,0.00009930378,0.0001218062,0.0001529101,0.00009372693],"domain_scores_gemma":[0.9986427,0.0001626158,0.00006051346,0.0008334609,0.000228033,0.00007272208],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001691261,0.00009623924,0.9846901,0.00003254459,0.00005678579,0.00000119469,0.0003336037,0.000002063892,0.006337057,0.007628341,0.00009317708,0.0005597578],"study_design_scores_gemma":[0.0003126948,0.0002404778,0.9962581,0.00003643225,0.00002626535,0.000006274926,0.00003919049,0.0006553824,0.001047338,0.0001498358,0.00118081,0.00004717765],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937888,0.001675829,0.00004495359,0.0038645,0.000009890872,0.0002372339,0.00005446406,0.0000150232,0.0003092874],"genre_scores_gemma":[0.9973565,0.0004324655,0.00187456,0.0002361908,0.00002226812,0.00001081272,0.00002675843,0.00000706302,0.00003336035],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01156801,"threshold_uncertainty_score":0.6027592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08304505900666616,"score_gpt":0.370645563117148,"score_spread":0.2876005041104819,"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."}}