{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001184674,0.00008978538,0.0002007226,0.0002483758,0.0001871558,0.00008146875,0.0001495026,0.00003830526,0.00005489441],"category_scores_gemma":[0.0005757729,0.00005509914,0.00007937024,0.0005390162,0.0001499921,0.00022048,0.00002642539,0.0002176773,3.88794e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003891415,"about_ca_system_score_gemma":0.00003322708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003280932,"about_ca_topic_score_gemma":0.003056671,"domain_scores_codex":[0.9988227,0.0002535072,0.0002617125,0.00009663095,0.0004279555,0.0001375261],"domain_scores_gemma":[0.9991658,0.0001999095,0.0002697435,0.0001549313,0.0001523267,0.00005726218],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.000385423,0.0002356917,0.1600012,0.0003412358,0.0002727154,0.00031193,0.5183241,0.00224884,0.0009319392,0.2632202,0.005152798,0.04857391],"study_design_scores_gemma":[0.0005591358,0.00004243383,0.4618253,0.0005943183,0.000117354,0.000002573181,0.5350835,0.0002624113,0.0001208705,0.0001773797,0.001061297,0.0001534398],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9800301,0.001172775,0.000001401174,0.001098298,0.0002439212,0.0000965459,0.000005348792,0.00002086019,0.01733081],"genre_scores_gemma":[0.9989375,0.0001336029,0.00001792961,0.00004380574,0.0004107301,0.000002089914,0.000009870308,0.000006381615,0.000438079],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3018241,"threshold_uncertainty_score":0.2246878,"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."}}