{"id":"W4410357290","doi":"10.31234/osf.io/54vxh_v1","title":"Patterns of pre-nasal allophony across dialects of English: A multi-corpus study of the /ɪ/-/ɛ/ contrast","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Linguistic Variation and Morphology","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Contrast (vision); Linguistics; Computer science; Artificial intelligence; Philosophy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004174497,0.0002082342,0.0003666077,0.001044793,0.0008123945,0.0008450783,0.0002545403,0.0003572244,0.001094269],"category_scores_gemma":[0.00140771,0.0002131618,0.0001925085,0.0008868619,0.0005600199,0.0005957125,0.001110965,0.000326883,0.0002977003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002503034,"about_ca_system_score_gemma":0.0001396213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009873625,"about_ca_topic_score_gemma":0.03723858,"domain_scores_codex":[0.999626,0.00009575226,0.0000434873,0.0001253378,0.00006338551,0.00004595584],"domain_scores_gemma":[0.9984424,0.0007178411,0.0002612763,0.0001594,0.0003021946,0.000116917],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001111784,0.000262168,0.5286234,0.0005499875,0.0003699736,0.001657153,0.08248823,0.0002776619,0.3230339,0.0005658159,0.000625703,0.06043423],"study_design_scores_gemma":[0.000005936372,0.00007439886,0.9877713,0.00001081299,0.0000391007,0.0005947922,0.007162487,0.00018475,0.002967858,0.00004476142,0.00112663,0.00001715203],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999184,0.0001063279,0.0001139885,0.000008656715,0.000001571012,0.000004412605,0.00008754955,0.000003269028,0.000490254],"genre_scores_gemma":[0.9990029,0.00007074929,0.00031633,0.00001902264,0.000003263596,0.00001058211,0.0002443355,0.00001392912,0.0003189752],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009873625,"threshold_uncertainty_score":0.01963234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03461772887468383,"score_gpt":0.3522081688425587,"score_spread":0.3175904399678748,"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."}}