{"id":"W3128155389","doi":"10.37213/cjal.2021.28995","title":"A Corpus Study of the English Suffixes -ness and -acy: Productivity, Genre, and Implications for L2 Learning","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Applied Linguistics","topic":"Second Language Acquisition and Learning","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; National Science Foundation","keywords":"Corpus linguistics; Linguistics; Productivity; Noun; Competence (human resources); Scholarship; British National Corpus; Psychology; Sociology; Political science; Philosophy; Economics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":true,"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":[0.00292542,0.0002563049,0.0004709815,0.004202425,0.003419088,0.002173177,0.0005203405,0.0005278398,0.003437942],"category_scores_gemma":[0.01066153,0.0002213866,0.0001547822,0.006036651,0.002948707,0.002723336,0.003257439,0.001209981,0.0005468092],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001631815,"about_ca_system_score_gemma":0.001666555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008629313,"about_ca_topic_score_gemma":0.03028154,"domain_scores_codex":[0.9988285,0.0004496989,0.0001283911,0.0002779314,0.0002588239,0.00005666661],"domain_scores_gemma":[0.9862315,0.008869546,0.001619023,0.001136822,0.001672988,0.0004701272],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0004711982,0.0006640026,0.2125548,0.002245662,0.00006084627,0.001808644,0.5068324,0.0001775429,0.01533709,0.03687417,0.01562073,0.2073529],"study_design_scores_gemma":[0.00005906829,0.0002958902,0.5392246,0.0007473828,0.00008478452,0.002862538,0.2630916,0.0008735945,0.006276751,0.005435726,0.1809498,0.00009834173],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9778212,0.001646721,0.002130545,0.000555391,0.00004089259,0.0001897445,0.00183805,0.00002334584,0.01575399],"genre_scores_gemma":[0.9824603,0.00139513,0.006784896,0.0002440713,0.00005402224,0.0004903083,0.002246058,0.00008634221,0.006238789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008629313,"threshold_uncertainty_score":0.01715821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01944734172946509,"score_gpt":0.2835125523093456,"score_spread":0.2640652105798805,"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."}}