{"id":"W2929826240","doi":"10.1017/s1366728919000014","title":"Triggered codeswitching: Lexical processing and conversational dynamics","year":2019,"lang":"en","type":"article","venue":"Bilingualism Language and Cognition","topic":"Neurobiology of Language and Bilingualism","field":"Neuroscience","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Max Planck Instituut voor Psycholinguïstiek; British Academy","keywords":"Context (archaeology); Linguistics; Computer science; Lexical item; Speech production; Psychology; Welsh; Natural language processing; Speech recognition; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002062678,0.0001753793,0.0001996781,0.000105013,0.0001578862,0.00009828577,0.00008314733,0.0001290629,0.0001230259],"category_scores_gemma":[0.0002449439,0.0001519416,0.00003906981,0.0001273625,0.0001833883,0.0002039131,0.00006007962,0.0002051066,0.00003051577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001413494,"about_ca_system_score_gemma":0.00004763642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002048315,"about_ca_topic_score_gemma":0.00001442813,"domain_scores_codex":[0.9987225,0.0001164781,0.0002222149,0.0005245031,0.0001757115,0.0002386194],"domain_scores_gemma":[0.9993631,0.0002754821,0.0001036621,0.0001272824,0.00004307241,0.0000873677],"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":[0.0002343112,0.0001426154,0.0009752838,0.000215077,0.00001289101,0.000716123,0.0131235,0.000001538805,0.8972548,0.004063435,0.00002803816,0.08323239],"study_design_scores_gemma":[0.01544213,0.001446137,0.003238221,0.000734188,0.000434674,0.01149972,0.04287019,0.03522077,0.8606151,0.02288474,0.002299553,0.003314576],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996331,0.0004106238,0.00009053474,0.0003044866,0.0001227945,0.0002904414,0.0000377126,0.0001262188,0.002286143],"genre_scores_gemma":[0.9962176,0.0000548481,0.0001530975,0.002840898,0.0001290068,0.000007523573,0.00007636028,0.00001915713,0.0005014854],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07991781,"threshold_uncertainty_score":0.6195999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0174203726603213,"score_gpt":0.2733394122516737,"score_spread":0.2559190395913524,"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."}}