{"id":"W2186100321","doi":"","title":"Assessing contact-induced language change: The use of subject relative markers in Quebec English ∗","year":2011,"lang":"en","type":"article","venue":"","topic":"Linguistic Variation and Morphology","field":"Social Sciences","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mainstream; Language contact; Linguistics; Language change; Varieties of English; Variety (cybernetics); Neuroscience of multilingualism; American English; Convergence (economics); Subject (documents); Multivariate statistics; English language; Psychology; British English; Computer science; Mathematics; Political science; Statistics; Artificial intelligence; Law; Economics","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":[0.001977883,0.0002476379,0.0002959255,0.001525385,0.00219562,0.001169975,0.0006593968,0.0004374541,0.001791334],"category_scores_gemma":[0.007101931,0.0001428846,0.0002091848,0.001662179,0.001400962,0.0005416449,0.0009160042,0.0003748517,0.0001267226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009020859,"about_ca_system_score_gemma":0.00491185,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9058194,"about_ca_topic_score_gemma":0.9555401,"domain_scores_codex":[0.9986134,0.000347689,0.00006316177,0.0002828412,0.0004878704,0.0002050589],"domain_scores_gemma":[0.9956234,0.00124466,0.0008311674,0.0003035867,0.001687232,0.0003098996],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005074376,0.00008767214,0.8762493,0.0001137073,0.0001136484,0.0005192899,0.06154456,0.0003163588,0.02180513,0.0007256159,0.0003236862,0.03769362],"study_design_scores_gemma":[0.000001893808,0.00006377754,0.9920734,0.000007715505,0.00001206767,0.00006966168,0.006074505,0.0001551789,0.0008077868,0.00003571419,0.0006852124,0.00001314566],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982191,0.00008793906,0.0001604304,0.00002996716,0.000002107875,0.00001478034,0.0001228885,0.00000355156,0.001359188],"genre_scores_gemma":[0.9989455,0.00003226076,0.0002493426,0.00001238346,8.930446e-7,0.000009654241,0.0001138013,0.0000032052,0.000632997],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09418058,"threshold_uncertainty_score":0.1894704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1619047235298908,"score_gpt":0.3524381145825763,"score_spread":0.1905333910526855,"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."}}