{"id":"W2579891069","doi":"","title":"Past tense formation with irregular lexical verbs in Canadian English","year":2013,"lang":"en","type":"article","venue":"QSpace (Queen's University Library)","topic":"Linguistic Variation and Morphology","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Linguistics; Past tense; American English; Casual; Present tense; Variation (astronomy); Psychology; History; North American English; Set (abstract data type); Modal verb; British English; Categorical variable; Verb; Computer science","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":[0.0006974891,0.0003233576,0.0002761456,0.002413949,0.005260872,0.002506714,0.0005238131,0.0003032575,0.002409467],"category_scores_gemma":[0.003102862,0.0002837537,0.0002083896,0.003476023,0.00392977,0.0007667891,0.001292693,0.0006751051,0.0001830998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01433,"about_ca_system_score_gemma":0.0113667,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9329253,"about_ca_topic_score_gemma":0.9730319,"domain_scores_codex":[0.9991539,0.0001051102,0.0000493527,0.0001490092,0.00035224,0.000190512],"domain_scores_gemma":[0.997916,0.0005466912,0.0003588694,0.0001345314,0.0008150248,0.0002288375],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0003246149,0.00006618516,0.1359899,0.0003414204,0.00003697034,0.001829347,0.69809,0.0004410591,0.03175558,0.0421392,0.003660453,0.08532528],"study_design_scores_gemma":[0.00001641255,0.00007379019,0.6321967,0.0001996862,0.00008480436,0.002642245,0.2485792,0.001173818,0.004152451,0.002386175,0.1082825,0.0002122695],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.972315,0.0004233243,0.0005489141,0.0001955202,0.00001255272,0.0000185229,0.0002741901,0.00002355584,0.02618845],"genre_scores_gemma":[0.9974104,0.0002109299,0.0003622991,0.00002099348,0.000002341051,0.000004297061,0.0001303584,0.00001568734,0.001842743],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06707466,"threshold_uncertainty_score":0.1349393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006153369665087549,"score_gpt":0.1842706718240438,"score_spread":0.1781173021589563,"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."}}