{"id":"W4388960517","doi":"10.5430/wjel.v13n9p40","title":"System-structural and Functional-semantic Features of Motion Verbs in Sports Discourse Based on the Kazakh, Russian and English Languages","year":2023,"lang":"en","type":"article","venue":"World Journal of English Language","topic":"Discourse Analysis and Cultural Communication","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Linguistics; Computer science; Syntax; Grammar; Kazakh; Pragmatics; Natural language processing; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"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":[0.0004249737,0.0002002461,0.0001632659,0.001155565,0.0007799649,0.001722388,0.0001831026,0.0003032245,0.003007543],"category_scores_gemma":[0.001167753,0.0001048657,0.0001997706,0.0007347413,0.002387122,0.001633118,0.0008604557,0.0003568136,0.0001957331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001264748,"about_ca_system_score_gemma":0.0004186209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004969679,"about_ca_topic_score_gemma":0.003698062,"domain_scores_codex":[0.9996338,0.000189463,0.00002830227,0.0000575932,0.0000433029,0.00004747057],"domain_scores_gemma":[0.9995524,0.0002474284,0.0000961757,0.0000227932,0.00005590924,0.00002524104],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0007492564,0.0001032201,0.06124352,0.000934195,0.00006815964,0.002303394,0.3100312,0.001614357,0.0605676,0.5169927,0.00155764,0.04383473],"study_design_scores_gemma":[0.00009449013,0.0003052385,0.5159248,0.0005165137,0.0001888674,0.002603546,0.3104695,0.01363029,0.01179469,0.09520874,0.04914042,0.0001228483],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9684886,0.0004673861,0.002742433,0.0003953397,0.00001182989,0.00001699349,0.0001457456,0.00003044907,0.02770128],"genre_scores_gemma":[0.9989778,0.00004596499,0.0003352976,0.00001015692,0.000002270874,0.000006316569,0.00005006374,0.000004985441,0.0005671891],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004969679,"threshold_uncertainty_score":0.0100612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009492874019517827,"score_gpt":0.2804291337379822,"score_spread":0.2709362597184644,"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."}}