{"id":"W2945539495","doi":"10.1215/00031283-7603207","title":"Unlocking the Mystery of Dialect B","year":2019,"lang":"en","type":"article","venue":"American Speech","topic":"Linguistic Variation and Morphology","field":"Social Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Raising (metalworking); Variety (cybernetics); Nike; Linguistics; History; Psychology; Computer science; Philosophy; Mathematics; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0008676581,0.0002174998,0.0002053782,0.0007632494,0.001882969,0.001617956,0.000377551,0.0003723655,0.001433233],"category_scores_gemma":[0.001332153,0.0001570348,0.00009298495,0.0005324122,0.003019298,0.001635814,0.002028892,0.001039152,0.0001905719],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001322319,"about_ca_system_score_gemma":0.001420062,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06293684,"about_ca_topic_score_gemma":0.1088845,"domain_scores_codex":[0.9993567,0.0001596909,0.00004616121,0.0002877742,0.00006287649,0.00008685674],"domain_scores_gemma":[0.9993032,0.0001981415,0.0001180989,0.0001059427,0.0001497721,0.0001249266],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0005692341,0.00007042324,0.2464411,0.0002946481,0.0001021363,0.002278372,0.2339489,0.0002035358,0.04653865,0.1686758,0.004774469,0.2961026],"study_design_scores_gemma":[0.00002907182,0.0002279936,0.5753839,0.0003555344,0.00006741008,0.005864539,0.2116222,0.0009174417,0.007839289,0.03049546,0.1670683,0.0001287689],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9663553,0.0017802,0.002954567,0.002559924,0.0001109738,0.00001275617,0.00009571574,0.00002695092,0.02610371],"genre_scores_gemma":[0.9976024,0.0002843081,0.0006786584,0.0003043381,0.00001455511,0.000004357858,0.00002726289,0.00002152529,0.001062711],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06293684,"threshold_uncertainty_score":0.125141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01459791080942901,"score_gpt":0.3072546323636787,"score_spread":0.2926567215542497,"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."}}