{"id":"W95065317","doi":"","title":"Errors in speech production: Explaining mismatch and accommodation","year":2009,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Neurobiology of Language and Bilingualism","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Carleton University","funders":"","keywords":"Speech recognition; Speech error; Consonant; Voice; Syllabification; Computer science; Speech production; Coda; Syllable; Linguistics; Acoustics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001356932,0.0007181265,0.0004360587,0.001117182,0.0003444211,0.001455213,0.0009434632,0.00155011,0.00239968],"category_scores_gemma":[0.01051473,0.0005442877,0.0004984677,0.0004597579,0.002637761,0.002625763,0.00237512,0.0008302542,0.0005487953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005699114,"about_ca_system_score_gemma":0.0004076757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002091002,"about_ca_topic_score_gemma":0.000734506,"domain_scores_codex":[0.9993017,0.0002202393,0.00007296495,0.0001667921,0.0001481079,0.00009014825],"domain_scores_gemma":[0.9958067,0.002367144,0.0006799815,0.0006606358,0.0003284239,0.0001571164],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003218214,0.0005059709,0.3213249,0.0008718349,0.0001803756,0.01254977,0.01688464,0.1324265,0.06711084,0.236296,0.001864019,0.206767],"study_design_scores_gemma":[0.0001248557,0.0003937708,0.06217137,0.00008516671,0.00009275422,0.007184308,0.002126621,0.6232346,0.01694994,0.2850299,0.002480103,0.000126641],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7872092,0.0008819073,0.1973075,0.001578193,0.00008218414,0.00006725423,0.0001842036,0.0005656969,0.01212395],"genre_scores_gemma":[0.9942589,0.000135533,0.004747543,0.00003256399,0.00001321521,0.00001348165,0.00003153797,0.00003143249,0.0007359431],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00239968,"threshold_uncertainty_score":0.008027732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02517216989514924,"score_gpt":0.2515171284288469,"score_spread":0.2263449585336977,"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."}}