{"id":"W1940459719","doi":"10.1002/9780470027318.a0109","title":"Magnetic Resonance Imaging, Functional","year":2000,"lang":"en","type":"other","venue":"Encyclopedia of Analytical Chemistry","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Functional magnetic resonance imaging; Electroencephalography; Neuroimaging; Computer science; Independent component analysis; Artificial intelligence; Stimulus (psychology); Brain activity and meditation; Pattern recognition (psychology); EEG-fMRI; Functional imaging; Positron emission tomography; Neuroscience; Psychology; Cognitive psychology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00002158655,0.0002120084,0.0003684433,0.00004619288,0.00001511453,0.000003049659,0.0001072043,0.0002124131,0.03006484],"category_scores_gemma":[0.00002702538,0.0001996486,0.0001498435,0.0001558439,0.0002078939,0.00001030011,0.00003049353,0.000299897,0.0000725471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002498578,"about_ca_system_score_gemma":0.0001068102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001197731,"about_ca_topic_score_gemma":6.328602e-7,"domain_scores_codex":[0.9989414,0.000003201638,0.0002651205,0.0003478287,0.0002496638,0.0001928365],"domain_scores_gemma":[0.99924,0.00002285855,0.00008999309,0.0004720713,0.00002648934,0.000148534],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002274941,0.0001207674,0.0003675631,0.0001156351,0.000005793305,0.00001883038,0.000001615847,5.244004e-7,0.00008260392,0.0001135888,0.9894183,0.009732036],"study_design_scores_gemma":[0.000265211,0.00001780673,0.0003704567,0.0002283122,0.0001305158,0.00003527126,0.000003603914,0.0001095924,0.0002227418,0.0002195479,0.9982252,0.0001717374],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00001496188,0.005810337,0.0008692192,0.000269382,0.00001883467,0.0001550448,0.00008863955,0.0001845763,0.992589],"genre_scores_gemma":[0.00009173991,0.003431916,0.005707245,0.0001125664,0.0006296958,0.0000348915,0.0001958836,0.0001798711,0.9896162],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.0299923,"threshold_uncertainty_score":0.9708218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00728042455949671,"score_gpt":0.2652799715410696,"score_spread":0.2579995469815728,"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."}}