{"id":"W2158165330","doi":"10.5539/ijel.v3n5p29","title":"The Translation Strategy of Advertisement based on Nonequivalence between Chinese and English Conceptual Metaphors","year":2013,"lang":"en","type":"article","venue":"International Journal of English Linguistics","topic":"Language, Metaphor, and Cognition","field":"Psychology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Education of the People's Republic of China","keywords":"Metaphor; Conceptual metaphor; Embodied cognition; Preference; Translation (biology); Psychology; Linguistics; Cognition; Advertising; Computer science; Function (biology); Artificial intelligence; Mathematics; Business; 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":[0.004688219,0.0004581498,0.0002789441,0.001044601,0.003010531,0.003019271,0.0005238898,0.0005963615,0.002420527],"category_scores_gemma":[0.01017998,0.0002257517,0.0002402612,0.001079082,0.005389729,0.003301989,0.001733074,0.001418242,0.0002091799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001853313,"about_ca_system_score_gemma":0.002500321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002647864,"about_ca_topic_score_gemma":0.00195585,"domain_scores_codex":[0.9950598,0.00361541,0.0001860087,0.0002370744,0.0006339099,0.0002677831],"domain_scores_gemma":[0.9959958,0.002632525,0.0003232925,0.0002636407,0.0006081711,0.0001765689],"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":[0.00008832053,0.00004608144,0.004608045,0.000213302,0.000007989979,0.001155776,0.9300953,0.00006659463,0.006083902,0.03869744,0.0007377197,0.01819961],"study_design_scores_gemma":[0.00004688883,0.0001768935,0.02350113,0.0002473071,0.00005573414,0.002698836,0.8996731,0.002332385,0.006556996,0.01063501,0.05400211,0.00007356107],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9619177,0.0004863194,0.006509367,0.001331,0.00009922249,0.0001156172,0.00002351297,0.00002566299,0.02949172],"genre_scores_gemma":[0.9966079,0.00008426297,0.001409189,0.0001051215,0.000008480048,0.00002284169,0.00001071821,0.0000129641,0.001738624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004688219,"threshold_uncertainty_score":0.02479398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02486847898684765,"score_gpt":0.3118358945665769,"score_spread":0.2869674155797293,"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."}}