{"id":"W2030222967","doi":"10.1016/j.neulet.2010.12.055","title":"Localization of Broca's area using verb generation tasks in the MEG: Validation against fMRI","year":2010,"lang":"en","type":"article","venue":"Neuroscience Letters","topic":"Neurobiology of Language and Bilingualism","field":"Neuroscience","cited_by":81,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; SickKids Foundation; Hospital for Sick Children","funders":"Canadian Institutes of Health Research","keywords":"Voxel; Functional magnetic resonance imaging; Magnetoencephalography; Psychology; Verb; Concordance; Lateralization of brain function; Insula; Task (project management); Broca's area; Laterality; Artificial intelligence; Neuroscience; Computer science; Electroencephalography; Medicine","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":[0.0003865198,0.0001272593,0.0001127765,0.000130598,0.0002090687,0.0000778729,0.00049374,0.00006329879,0.000005659108],"category_scores_gemma":[0.0007573687,0.00009540038,0.00004311533,0.0006707133,0.0004097144,0.0003455528,0.00004607256,0.0002882123,0.000002554375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001216182,"about_ca_system_score_gemma":0.00003277726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003720421,"about_ca_topic_score_gemma":0.00002921382,"domain_scores_codex":[0.9984092,0.0002651477,0.0002738214,0.000455143,0.000344054,0.0002526963],"domain_scores_gemma":[0.9993023,0.0001362885,0.0001675961,0.0003401442,0.00002356057,0.00003012495],"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":[0.000003864867,0.00003692976,0.001089146,0.000003611922,1.11917e-7,0.00006520849,0.0004790539,0.005509463,0.992217,0.0000488963,0.0002025375,0.0003441526],"study_design_scores_gemma":[0.0001760491,0.00003640007,0.0003935768,0.000006508768,0.000004402011,0.0001177128,0.00003429911,0.0381949,0.9600589,0.00002004676,0.0008422679,0.0001149892],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937244,0.000003350349,0.002985954,0.001922508,0.001036436,0.0002284256,0.000005110964,0.00002712094,0.00006670746],"genre_scores_gemma":[0.9647366,0.000009020473,0.00008822625,0.03502373,0.0001188535,0.000005491878,0.000005066204,0.000008989471,0.000004060613],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03310122,"threshold_uncertainty_score":0.3890314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06063041523383548,"score_gpt":0.2949949748067223,"score_spread":0.2343645595728868,"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."}}