{"id":"W2010408890","doi":"10.1016/j.neuroimage.2004.05.018","title":"Spatiotemporal analysis of event-related fMRI data using partial least squares","year":2004,"lang":"en","type":"article","venue":"NeuroImage","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":347,"is_retracted":false,"has_abstract":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"Canadian Institutes of Health Research; James S. McDonnell Foundation","keywords":"Univariate; Partial least squares regression; Resampling; Functional magnetic resonance imaging; Artificial intelligence; Computer science; Multivariate statistics; Neuroimaging; Pattern recognition (psychology); Psychology; Machine learning; Neuroscience","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":[0.0002157827,0.0001583842,0.0003103329,0.0002867534,0.0001883417,0.00003794316,0.0004316599,0.00004356823,0.00008139511],"category_scores_gemma":[0.004418067,0.0001582627,0.0001274159,0.001483602,0.0002294786,0.0004690478,0.000391789,0.0001686909,0.00002587779],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004156592,"about_ca_system_score_gemma":0.00008698972,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003658047,"about_ca_topic_score_gemma":0.0001351758,"domain_scores_codex":[0.9980814,0.0001687474,0.0003460828,0.0007254795,0.0004413688,0.0002369308],"domain_scores_gemma":[0.9980704,0.0007763958,0.0002026532,0.0008438323,0.00005226094,0.00005452672],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001280633,0.0004805637,0.01687106,0.00003092917,0.000292176,0.0001580637,0.0003485102,0.09430335,0.8837925,0.002129249,0.0006418056,0.0008237811],"study_design_scores_gemma":[0.003283089,0.0005597771,0.2399539,0.00007048537,0.002225301,0.00007033467,0.0001844248,0.2747795,0.4727083,0.001574611,0.003571205,0.001019017],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939558,0.00003042724,0.002717688,0.001948922,0.0003646746,0.0001568383,0.0002603868,0.00008385479,0.0004814195],"genre_scores_gemma":[0.9990937,0.00000641402,0.0002079723,0.0005473397,0.00004651829,0.000002232554,0.00002817935,0.0000183369,0.00004929562],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4110841,"threshold_uncertainty_score":0.6453766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1167718652115018,"score_gpt":0.3367767946479234,"score_spread":0.2200049294364215,"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."}}