{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0005117723,0.0001368398,0.0002127306,0.0001338138,0.00005165449,0.00006616794,0.0003178258,0.00007942311,0.0003007269],"category_scores_gemma":[0.01096432,0.00009360353,0.0001169027,0.00008436101,0.0001589191,0.0000708607,0.00001573469,0.0002702915,0.000004476249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003077193,"about_ca_system_score_gemma":0.00005280692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004378263,"about_ca_topic_score_gemma":0.000006728614,"domain_scores_codex":[0.9983552,0.0001434518,0.0006521804,0.0001296465,0.0005752199,0.00014433],"domain_scores_gemma":[0.9890537,0.0009426978,0.000491311,0.0001279451,0.009299903,0.00008450545],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.004104843,0.003152978,0.2234933,0.0001713263,0.007443919,0.0002744589,0.1130613,0.005460269,0.0008478095,0.1093032,0.01964828,0.5130383],"study_design_scores_gemma":[0.02346414,0.00577575,0.713615,0.0009390402,0.001720287,0.00001284047,0.04768127,0.004339795,0.004828668,0.0299507,0.1658981,0.001774393],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9218019,0.001304992,0.001941649,0.00006487364,0.01640409,0.0003069588,0.0001321224,0.00002533261,0.05801807],"genre_scores_gemma":[0.993932,0.00006603093,0.0003548905,0.00008510653,0.005468786,0.000006501984,0.00001946976,0.00001355054,0.00005365097],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5112639,"threshold_uncertainty_score":0.9973667,"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."}}