{"id":"W3047396807","doi":"10.1007/978-3-030-45623-8_10","title":"Combining Noninvasive Electromagnetic and Hemodynamic Measures of Human Brain Activity","year":2020,"lang":"en","type":"book-chapter","venue":"","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre","funders":"National Institutes of Health; Suomen Kulttuurirahasto; National Center for Research Resources; Tekniikan Edistämissäätiö; Novocure","keywords":"Magnetoencephalography; Electroencephalography; Neuroscience; Neuroimaging; Brain activity and meditation; Human brain; Functional magnetic resonance imaging; EEG-fMRI; Brain mapping; Computer science; Premovement neuronal activity; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005646801,0.0006561158,0.0004334199,0.001347127,0.000153795,0.001738606,0.0005277611,0.0009423309,0.009340933],"category_scores_gemma":[0.0005403542,0.0002716758,0.0002587338,0.001181025,0.0006434341,0.001884439,0.0007704998,0.0007934206,0.006331429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003743036,"about_ca_system_score_gemma":0.0002599524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003451377,"about_ca_topic_score_gemma":0.0007427,"domain_scores_codex":[0.999779,0.00003781568,0.00000900285,0.00006329529,0.0001033146,0.000007451307],"domain_scores_gemma":[0.9998162,0.0001181055,0.00001167607,0.000009586044,0.00003686704,0.000007565884],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000042286,0.00004153817,0.0004767637,0.001487587,0.00005079748,0.0002592808,0.0001754415,0.001763307,0.02703495,0.09624232,0.05097225,0.8214535],"study_design_scores_gemma":[0.000007827189,0.0001075442,0.001932174,0.0007792001,0.00005030093,0.002229046,0.0001189475,0.006256731,0.01275226,0.1210818,0.8546317,0.00005231537],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006644327,0.2546811,0.3920247,0.004670599,0.003224971,0.0001578609,0.0006560436,0.001501325,0.3364391],"genre_scores_gemma":[0.06419283,0.2057592,0.3532161,0.003843452,0.005862632,0.0002805266,0.0008598748,0.0006325112,0.3653529],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009340933,"threshold_uncertainty_score":0.03124857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05580656752278734,"score_gpt":0.2546735253782199,"score_spread":0.1988669578554325,"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."}}