{"id":"W2979066753","doi":"10.3968/11282","title":"Aesthetic Representation in English to Chinese Translation of Business Letter","year":2019,"lang":"en","type":"article","venue":"Canadian social science","topic":"Translation Studies and Practices","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Perspective (graphical); Representation (politics); Business English; Sentence; Linguistics; Translation (biology); Computer science; Natural language processing; Artificial intelligence; Political science; Law; Politics; 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":[0.00121658,0.0003895964,0.0001880346,0.0009887844,0.002352499,0.002649258,0.0002471843,0.0003277508,0.005702656],"category_scores_gemma":[0.004328143,0.0001151075,0.0002070673,0.001520403,0.004189278,0.001497905,0.001291066,0.0009828471,0.0005515369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00343871,"about_ca_system_score_gemma":0.002250372,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01510169,"about_ca_topic_score_gemma":0.01238223,"domain_scores_codex":[0.9983503,0.0008082545,0.00007740843,0.0001303437,0.000446766,0.0001869844],"domain_scores_gemma":[0.9982698,0.000664484,0.0001795986,0.0001795787,0.0006235254,0.00008300907],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004934705,0.00009002635,0.01090534,0.0004217485,0.00001391787,0.003617854,0.559689,0.0007467374,0.01958818,0.2679234,0.0129904,0.12352],"study_design_scores_gemma":[0.00006642632,0.0003789385,0.1144401,0.0006794854,0.00008638395,0.004499064,0.4604079,0.01304208,0.02356439,0.05141587,0.3312211,0.0001982371],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7111484,0.0005984584,0.01075476,0.002907948,0.0004701948,0.00008644136,0.0001814689,0.0001235891,0.2737288],"genre_scores_gemma":[0.9889318,0.0001384097,0.001453693,0.0001320642,0.00004083772,0.00001681478,0.00006872913,0.00005590006,0.00916184],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01510169,"threshold_uncertainty_score":0.03002763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03245748098692724,"score_gpt":0.2750337182332682,"score_spread":0.242576237246341,"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."}}