{"id":"W1990020440","doi":"10.1075/ml.6.1.06ste","title":"The EEG/ERP technologies in linguistic research","year":2011,"lang":"en","type":"article","venue":"The Mental Lexicon","topic":"Neurobiology of Language and Bilingualism","field":"Neuroscience","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Université de Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"University of California, Davis","keywords":"Electroencephalography; Neuroimaging; Computer science; Functional magnetic resonance imaging; Field (mathematics); EEG-fMRI; Psychology; Cognitive science; Neuroscience","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":[0.0006876209,0.00008306154,0.00007466849,0.00006736998,0.0004609668,0.00003182773,0.0008102112,0.00005480432,0.00002867024],"category_scores_gemma":[0.001291609,0.00004057412,0.0000288659,0.0002594504,0.001094643,0.0000298963,0.0003161561,0.0004663946,0.0001742687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002935979,"about_ca_system_score_gemma":0.0000233994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009668728,"about_ca_topic_score_gemma":0.0001061926,"domain_scores_codex":[0.9987535,0.0003197223,0.0001434437,0.0002437655,0.00016893,0.0003705819],"domain_scores_gemma":[0.9989058,0.0006277239,0.00003492769,0.0004023304,0.0000144279,0.00001478994],"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":[0.0001749989,0.0001457127,0.0007103716,0.000006514616,0.000003689819,0.0006430713,0.01342503,1.974119e-7,0.9409567,0.02732476,0.0005937996,0.01601519],"study_design_scores_gemma":[0.0002198414,0.0002020428,0.000595781,0.00001897172,0.000002240363,0.0001404408,0.004084628,0.0000204731,0.9461994,0.03958039,0.008837559,0.00009827837],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9743774,0.0003294882,3.798823e-7,0.001833366,0.0003817603,0.0002913909,0.0000032617,0.0001164518,0.02266651],"genre_scores_gemma":[0.9984308,0.0001602887,0.00001520672,0.0002740877,0.00002755701,0.00002539736,3.973369e-7,0.000008379801,0.001057821],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02405347,"threshold_uncertainty_score":0.4033258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.159303050204474,"score_gpt":0.3739242461455413,"score_spread":0.2146211959410673,"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."}}