{"id":"W3211923696","doi":"10.1002/jcv2.12042","title":"Ensemble classification of autism spectrum disorder using structural magnetic resonance imaging features","year":2021,"lang":"en","type":"article","venue":"JCPP Advances","topic":"Autism Spectrum Disorder Research","field":"Neuroscience","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"FP7 Health; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Canadian Institutes of Health Research; Horizon 2020 Framework Programme; National Institutes of Health; Centro de Investigación Biomédica en Red de Salud Mental; King's College London; Ministerio de Ciencia e Innovación; National Institute for Health and Care Research; European Regional Development Fund; U.S. Department of Defense; Sanofi; Alva Foundation; European Commission; Fondation Brain Canada; Fundación Alicia Koplowitz; Autism Speaks; European Federation of Pharmaceutical Industries and Associations; Instituto de Salud Carlos III; Simons Foundation Autism Research Initiative","keywords":"Autism spectrum disorder; Artificial intelligence; Receiver operating characteristic; Magnetic resonance imaging; Convolutional neural network; Machine learning; Functional magnetic resonance imaging; Computer science; Pattern recognition (psychology); Autism; Psychology; Medicine; Neuroscience; Radiology; Developmental psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003525041,0.001305745,0.001211414,0.003212075,0.0003826669,0.0009423628,0.0008144586,0.0009880089,0.0009388528],"category_scores_gemma":[0.006190341,0.0002244635,0.001442214,0.0007483367,0.0002900861,0.0007083265,0.0008896395,0.001112429,0.0005431442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007070704,"about_ca_system_score_gemma":0.0006492526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006511142,"about_ca_topic_score_gemma":0.005851747,"domain_scores_codex":[0.9990491,0.0002970528,0.00008211614,0.0003026965,0.00015608,0.0001129386],"domain_scores_gemma":[0.9967001,0.001832764,0.0003142934,0.0002935757,0.0006854639,0.0001738741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.001302871,0.0007207356,0.3270297,0.0001765682,0.0017161,0.0006004552,0.0002393102,0.3287014,0.007261792,0.0005593405,0.009276533,0.3224152],"study_design_scores_gemma":[0.00002633898,0.0002232098,0.02821158,0.00003996027,0.0002201087,0.0001847538,0.00007337605,0.9672016,0.001692998,0.001533293,0.0005604203,0.00003234921],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9119519,0.00220122,0.07961049,0.0007255215,0.0002193159,0.0001373753,0.001903828,0.001312133,0.001938248],"genre_scores_gemma":[0.9847314,0.000204911,0.01213818,0.00009440436,0.0000806739,0.00005386725,0.002209996,0.00003488082,0.0004516848],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006511142,"threshold_uncertainty_score":0.01864237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02357147568226942,"score_gpt":0.3176780705867669,"score_spread":0.2941065949044975,"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."}}