{"id":"W2741743121","doi":"","title":"'Toronto has everything', 'Toronto's got it all': Ethnolinguistic Dimensions of have in Toronto English","year":2014,"lang":"en","type":"article","venue":"","topic":"Linguistic Variation and Morphology","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Media studies; Sociology; History","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":[0.001262987,0.0002845567,0.0002902693,0.001672599,0.01091234,0.004628962,0.0006760248,0.0008108396,0.005930001],"category_scores_gemma":[0.003211446,0.0002743673,0.0001285186,0.003587945,0.01553931,0.002452049,0.002867191,0.00166893,0.0001980833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02495862,"about_ca_system_score_gemma":0.008358327,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8111154,"about_ca_topic_score_gemma":0.9176833,"domain_scores_codex":[0.9988936,0.0004428445,0.00004708711,0.0001254465,0.0001521021,0.0003390423],"domain_scores_gemma":[0.9980307,0.00086793,0.0003002394,0.0001448078,0.0003130212,0.0003431833],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00003095327,0.000004631874,0.007260764,0.00004737528,0.000006414605,0.0003327523,0.9276171,0.00004851804,0.0005691964,0.05964598,0.001237522,0.003198819],"study_design_scores_gemma":[0.000004921595,0.00001455397,0.06056529,0.0001282046,0.00003088184,0.0004096018,0.8900847,0.0001267746,0.00036378,0.003682479,0.04455825,0.00003058295],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8527081,0.001596945,0.0008609681,0.004433667,0.00006768925,0.00001557655,0.0002830385,0.00002053326,0.1400135],"genre_scores_gemma":[0.9976775,0.0001478965,0.0000712585,0.00005450188,0.000004799202,0.000002670745,0.00002245248,0.00001205602,0.002006877],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1888846,"threshold_uncertainty_score":0.379994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03637241351257126,"score_gpt":0.3388558905922758,"score_spread":0.3024834770797046,"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."}}