{"id":"W1143741088","doi":"10.1016/j.clinph.2015.08.005","title":"Electrocorticographic language mapping with a listening task consisting of alternating speech and music phrases","year":2015,"lang":"en","type":"article","venue":"Clinical Neurophysiology","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Electrocorticography; Active listening; Task (project management); Computer science; Speech recognition; Transcranial alternating current stimulation; Electroencephalography; Psychology; Transcranial magnetic stimulation; Communication; Neuroscience; Stimulation","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":[],"consensus_categories":[],"category_scores_codex":[0.000200287,0.0001529263,0.0004022084,0.00008938803,0.00005807372,0.00002709253,0.0002137002,0.00005717679,0.000004104977],"category_scores_gemma":[0.00193288,0.0001170877,0.00006613451,0.0002475431,0.0005531034,0.00007493403,0.000197441,0.0003354195,0.000005646904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000369345,"about_ca_system_score_gemma":0.00003861467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003212685,"about_ca_topic_score_gemma":0.000005532721,"domain_scores_codex":[0.9981064,0.0004051167,0.0005137341,0.0005491286,0.0001355567,0.0002900785],"domain_scores_gemma":[0.9973364,0.001962984,0.0003133214,0.0002025691,0.00005554536,0.0001291534],"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":[0.0001075371,0.0000815797,0.006353103,0.0000313269,0.00001183038,0.0002384153,0.0003749176,0.00003636631,0.9842434,0.00008442959,0.00003213213,0.008404984],"study_design_scores_gemma":[0.01014959,0.02065631,0.1094925,0.001105806,0.0002205701,0.00276161,0.002717809,0.06017368,0.7862115,0.002998712,0.001416308,0.00209555],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998851,0.00006023874,0.0002552282,0.00008325987,0.000222518,0.0001236919,0.000003098158,0.00007240877,0.0003285602],"genre_scores_gemma":[0.9966007,0.00001489823,0.001389272,0.001756051,0.0001928427,0.000002917327,0.000001016648,0.00001862939,0.00002362216],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1980319,"threshold_uncertainty_score":0.47747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08380069927556313,"score_gpt":0.3383365473039626,"score_spread":0.2545358480283995,"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."}}