{"id":"W2951037914","doi":"10.1080/00393274.2019.1616215","title":"Comparing explanatory principles of complement selection statistically: a case study based on Canadian English","year":2019,"lang":"en","type":"article","venue":"Studia Neophilologica","topic":"Syntax, Semantics, Linguistic Variation","field":"Arts and Humanities","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Linguistics; Variation (astronomy); Adjective; Negation; Alternation (linguistics); Complement (music); Multivariate statistics; Collinearity; Selection (genetic algorithm); Predicate (mathematical logic); Mathematics; Computer science; Natural language processing; Psychology; Econometrics; Statistics; Artificial intelligence; Noun; Philosophy","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":[0.004290128,0.0005950374,0.0005534975,0.004164745,0.006070253,0.002119996,0.001260475,0.001055285,0.002362774],"category_scores_gemma":[0.0195461,0.0002710019,0.0005272861,0.009524752,0.003770653,0.001006344,0.001661395,0.001004511,0.0002343002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0137554,"about_ca_system_score_gemma":0.01151718,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8892688,"about_ca_topic_score_gemma":0.9352968,"domain_scores_codex":[0.9960317,0.001723316,0.0001886206,0.0004837616,0.0009460282,0.0006265746],"domain_scores_gemma":[0.9778191,0.01702618,0.000954691,0.0009477111,0.002855696,0.0003966728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007695418,0.0009396236,0.6042448,0.0008643226,0.0003285311,0.01995234,0.1987417,0.003341725,0.004876789,0.0429488,0.009487998,0.1135038],"study_design_scores_gemma":[0.00006893736,0.000181469,0.6939852,0.0003530334,0.0003146407,0.005153087,0.2318352,0.008197092,0.004323673,0.007009752,0.04831858,0.000259406],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9909434,0.0005580952,0.001512581,0.0004147368,0.000008587736,0.0001246431,0.0009222615,0.00001749417,0.005498071],"genre_scores_gemma":[0.9933435,0.0004626059,0.003384402,0.00009796923,0.000009346001,0.00005131397,0.0009084804,0.00002907382,0.001713213],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1107312,"threshold_uncertainty_score":0.2227666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07828357769156175,"score_gpt":0.2676574659511027,"score_spread":0.189373888259541,"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."}}