{"id":"W7067583553","doi":"","title":"Machine Learning Methods for Structural Brain MRIs: Applications for Alzheimer’s Disease and Autism Spectrum Disorder","year":2017,"lang":"en","type":"other","venue":"Tampere University Institutional Repository (Tampere University)","topic":"Geochemistry and Elemental Analysis","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"H2020 European Research Council; Canadian Institutes of Health Research; University of California, San Diego; Genentech; National Institutes of Health; IXICO; H. Lundbeck A/S; Servier; Universidad Carlos III de Madrid; U.S. Department of Defense; Eli Lilly and Company; Compute Canada; China Scholarship Council; Eisai; Bristol-Myers Squibb; Ministerio de Economía y Competitividad; Meso Scale Diagnostics; Ministerio de Educación, Cultura y Deporte; Northern California Institute for Research and Education; European Commission; Fondation Brain Canada; Pfizer; Biogen; BioClinica; Synarc; University of Southern California; Medpace; Banco Santander; Novartis Pharmaceuticals Corporation; Alzheimer's Drug Discovery Foundation; Alzheimer's Disease Neuroimaging Initiative; Alzheimer's Association","keywords":"Neuroimaging; Feature selection; Disease; Autism spectrum disorder; Dimensionality reduction; Medical diagnosis; Feature (linguistics); Cognition; Neuropsychology","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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0001180805,0.0003593429,0.0003632039,0.000340483,0.002829858,0.00007965216,0.0005562216,0.00025368,0.0007101113],"category_scores_gemma":[0.00003744378,0.0003964547,0.0002889986,0.0001650737,0.0005658247,0.0002832458,0.00009145424,0.0002488764,0.00001006076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006485381,"about_ca_system_score_gemma":0.000294377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003642557,"about_ca_topic_score_gemma":0.002241115,"domain_scores_codex":[0.998549,0.0001078047,0.0001276787,0.0006981718,0.0001702802,0.0003470227],"domain_scores_gemma":[0.9987893,0.0001815632,0.0002958651,0.0003313264,0.00004882118,0.0003531335],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.007020071,0.0007648438,0.3931555,0.004643486,0.01660793,0.001708151,0.001085924,0.02348666,0.0008801767,0.2363688,0.1161098,0.1981687],"study_design_scores_gemma":[0.0008913922,0.00005775393,0.002244749,0.00006665984,0.0009121129,0.00002210308,0.0002573023,0.004986803,0.00001538758,0.0003396531,0.9897087,0.0004973336],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.004642345,0.01615235,0.1671049,0.004001977,0.001636366,0.006599093,0.01898191,0.001095688,0.7797853],"genre_scores_gemma":[0.05359697,0.0008519167,0.01469662,0.00006994916,0.000461789,0.000002422721,0.007600655,0.0000533091,0.9226664],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.8735989,"threshold_uncertainty_score":0.9998487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01117300593569872,"score_gpt":0.2329622987454834,"score_spread":0.2217892928097846,"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."}}