{"id":"W1977568486","doi":"10.7202/029792ar","title":"Analysing Irony for Translation","year":2009,"lang":"en","type":"article","venue":"Meta Journal des traducteurs","topic":"Translation Studies and Practices","field":"Arts and Humanities","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Irony; Linguistics; Utterance; Rhetorical question; Translation studies; Interpretation (philosophy); Computer science; 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":[0.005412131,0.0006913675,0.0006902204,0.002935097,0.005015764,0.006523343,0.0008953793,0.00206926,0.008359667],"category_scores_gemma":[0.0211926,0.0004326259,0.0005487363,0.002413927,0.01289026,0.00904704,0.004090089,0.002937009,0.001307207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004073574,"about_ca_system_score_gemma":0.002600615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002184185,"about_ca_topic_score_gemma":0.001688897,"domain_scores_codex":[0.993233,0.004257279,0.0002721218,0.0004445464,0.001313085,0.0004800201],"domain_scores_gemma":[0.9872906,0.008108375,0.00089902,0.001491939,0.002023216,0.00018692],"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":[0.00009672117,0.00004266185,0.002360965,0.0003023937,0.00001854443,0.001268103,0.05655029,0.0006473701,0.001183378,0.8905056,0.004966343,0.04205767],"study_design_scores_gemma":[0.00004334049,0.0001247475,0.005863307,0.0009645381,0.00004455867,0.001672507,0.04899241,0.008111005,0.00405513,0.6972727,0.2328016,0.00005413946],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2481851,0.005426233,0.15972,0.01814679,0.001191025,0.000260234,0.0003864738,0.000391677,0.5662924],"genre_scores_gemma":[0.9529311,0.0008976386,0.02204674,0.000659715,0.0002649205,0.0001198135,0.0003495417,0.0003176454,0.02241295],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008359667,"threshold_uncertainty_score":0.02955598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1431492995742896,"score_gpt":0.3138187471926104,"score_spread":0.1706694476183208,"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."}}