{"id":"W4401855966","doi":"10.1093/pnasnexus/pgae354","title":"When Jack isn’t Jacques: Simultaneous opposite language-specific speech perceptual learning in French–English bilinguals","year":2024,"lang":"en","type":"article","venue":"PNAS Nexus","topic":"Phonetics and Phonology Research","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Research on Brain Language and Music; Université du Québec à Montréal","funders":"H2020 European Research Council; Agencia Estatal de Investigación; Eusko Jaurlaritza; Social Sciences and Humanities Research Council of Canada; European Commission; Natural Sciences and Engineering Research Council of Canada; Ministerio de Ciencia e Innovación","keywords":"Categorization; Perception; Speech perception; Linguistics; Psychology; Term (time); Speech recognition; Computer science; Artificial intelligence","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0006323249,0.00028842,0.0003620491,0.0004302455,0.0001024712,0.00020619,0.0004697068,0.0003635785,0.01360847],"category_scores_gemma":[0.0003744939,0.0002810656,0.0001176432,0.0004839362,0.0002062885,0.00008595223,0.0001675456,0.001441912,0.003702393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001242054,"about_ca_system_score_gemma":0.00009781084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001615765,"about_ca_topic_score_gemma":0.0005249283,"domain_scores_codex":[0.9972559,0.0003491008,0.000422179,0.0008157884,0.0003063479,0.0008507213],"domain_scores_gemma":[0.9980214,0.001115515,0.00004330785,0.0005364169,0.0001039382,0.0001794549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002072641,0.000497969,0.003744596,0.0001302195,0.0002641333,0.01213444,0.705289,0.0009893827,0.02577868,0.001580762,0.06137807,0.1880055],"study_design_scores_gemma":[0.003024119,0.001738416,0.01564062,0.0004787619,0.00008137363,0.000643633,0.04825548,0.01009457,0.002912952,0.00459455,0.9106285,0.001907029],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.899617,0.01797044,0.00007765031,0.0003236346,0.002146071,0.0003391333,0.00003819619,0.0003936536,0.0790942],"genre_scores_gemma":[0.9608836,0.0002115786,0.0003181265,0.0001639445,0.0009529549,0.00003882404,0.0000720281,0.00008081472,0.03727813],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8492504,"threshold_uncertainty_score":0.9999642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02672202298507892,"score_gpt":0.33511924371491,"score_spread":0.3083972207298311,"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."}}