{"id":"W3033995920","doi":"10.1002/hbm.25092","title":"Divergence between functional magnetic resonance imaging and clinical indicators of language dominance in preoperative language mapping","year":2020,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Epilepsy research and treatment","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Discovery Centre; Nova Scotia Health Authority; Dalhousie University","funders":"","keywords":"Functional magnetic resonance imaging; Dominance (genetics); Laterality; Divergence (linguistics); Psychology; Magnetic resonance imaging; Wada test; Cognitive psychology; Epilepsy; Epilepsy surgery; Computer science; Medicine; Neuroscience; Radiology; Linguistics; Biology","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":[0.01692835,0.0007829566,0.0007491334,0.003193067,0.0008455233,0.002284114,0.0008800938,0.00163433,0.0008818683],"category_scores_gemma":[0.06409243,0.0003240003,0.0003446031,0.001338334,0.003968436,0.00331718,0.002420624,0.00186586,0.0006077648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007283957,"about_ca_system_score_gemma":0.001124111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009003904,"about_ca_topic_score_gemma":0.001160495,"domain_scores_codex":[0.9892069,0.004522101,0.00253281,0.0007667601,0.002381973,0.000589475],"domain_scores_gemma":[0.9700137,0.02023003,0.003190139,0.001521752,0.004444327,0.000600056],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001279876,0.0001077823,0.4529427,0.00101127,0.000181739,0.09702593,0.008753521,0.00229008,0.03706706,0.01607686,0.00456435,0.3786988],"study_design_scores_gemma":[0.0001124793,0.0008842237,0.3392659,0.002967253,0.0004391575,0.4946166,0.01159548,0.01287,0.02972557,0.07594243,0.03103111,0.0005498726],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7940915,0.03157721,0.1256092,0.01123722,0.0007650993,0.0003294246,0.0003446894,0.0005370209,0.03550882],"genre_scores_gemma":[0.9723693,0.003436839,0.0219663,0.001071401,0.0003161712,0.00008272324,0.0001386736,0.00008958319,0.0005290423],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01692835,"threshold_uncertainty_score":0.08952671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0420815968272418,"score_gpt":0.3371530727855921,"score_spread":0.2950714759583503,"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."}}