{"id":"W3081731064","doi":"10.1111/biom.13362","title":"Nonparametric matrix response regression with application to brain imaging data analysis","year":2020,"lang":"en","type":"article","venue":"Biometrics","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Simons Foundation","keywords":"Computer science; Nonparametric statistics; Neuroimaging; Covariance matrix; Algorithm; Artificial intelligence; Regression; Pattern recognition (psychology); Regularization (linguistics); Machine learning; Data mining; Mathematics; Econometrics; Statistics","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":[0.009738403,0.001234131,0.001782547,0.001713645,0.0005400304,0.001047653,0.001609754,0.001988881,0.002206551],"category_scores_gemma":[0.03010806,0.0007610081,0.001553522,0.002340377,0.001678396,0.001067769,0.001963417,0.002820844,0.001015314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000794014,"about_ca_system_score_gemma":0.001680734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004820737,"about_ca_topic_score_gemma":0.003525859,"domain_scores_codex":[0.9936706,0.004655501,0.0001757922,0.0005575604,0.000791202,0.0001493739],"domain_scores_gemma":[0.980604,0.0163529,0.0009783567,0.000840321,0.001067655,0.0001568992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001466789,0.0001273113,0.001376692,0.0002367031,0.0002449173,0.0002729238,0.0001417423,0.8123435,0.004026192,0.06279094,0.00203015,0.1162623],"study_design_scores_gemma":[0.00001052377,0.00002923123,0.0001803122,0.000006437853,0.000005725006,0.00004155292,0.000006544662,0.9820905,0.0003402949,0.01658575,0.0006882207,0.0000148665],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0014518,0.0001448133,0.9978727,0.0001358549,0.00001177738,0.00002168504,0.0000325527,0.0002052759,0.000123526],"genre_scores_gemma":[0.1706417,0.0009199878,0.8241707,0.0002440158,0.0002107212,0.0006120669,0.0004201196,0.0003418942,0.002438789],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009738403,"threshold_uncertainty_score":0.05150223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07158497471767379,"score_gpt":0.3443179850405773,"score_spread":0.2727330103229035,"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."}}