{"id":"W3163125471","doi":"10.1016/j.bandl.2021.104967","title":"Brain electrical dynamics in speech segmentation depends upon prior experience with the language","year":2021,"lang":"en","type":"article","venue":"Brain and Language","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Lethbridge","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Speech segmentation; Psychology; Segmentation; Stimulus (psychology); Speech perception; Perception; Sentence; Electroencephalography; First language; Dynamics (music); Speech recognition; Cognitive psychology; Linguistics; Communication; Natural language processing; Artificial intelligence; Computer science; Neuroscience","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":[0.0001765926,0.0001299279,0.0001239761,0.00006217032,0.00009881501,0.0001362771,0.0001871772,0.00004737761,0.00006670866],"category_scores_gemma":[0.000263842,0.0000862057,0.00002555498,0.000382141,0.00006609165,0.0001304376,0.00007910968,0.0002000177,0.000006224588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005175799,"about_ca_system_score_gemma":0.00003493566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001015625,"about_ca_topic_score_gemma":0.001931044,"domain_scores_codex":[0.9988174,0.0002048284,0.0001320773,0.0003715238,0.0002162082,0.0002579814],"domain_scores_gemma":[0.9991148,0.0005664379,0.00004611151,0.0002087047,0.0000114325,0.00005249441],"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":[0.00006593388,0.00009218376,0.001175243,0.00002003427,0.000004391497,0.001342796,0.03089289,0.0000087259,0.8715954,0.001380707,0.0005115646,0.09291012],"study_design_scores_gemma":[0.001290141,0.0002235284,0.005702335,0.00005743511,0.000006419954,0.0007819488,0.03313385,0.01266637,0.9446971,0.00003562633,0.001054159,0.0003511261],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928502,0.0002996174,0.0006270439,0.00447443,0.00004621162,0.0001575202,0.000009689425,0.00004922672,0.001486044],"genre_scores_gemma":[0.9912444,0.000009277303,0.0005064752,0.005625066,0.00004831509,0.00001556819,0.000009324237,0.00001378562,0.002527822],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09255899,"threshold_uncertainty_score":0.3515366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009413255557710248,"score_gpt":0.2778703492189515,"score_spread":0.2684570936612413,"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."}}