{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004181244,0.0001238121,0.0002408924,0.0001063408,0.0008527875,0.0004108414,0.00008852386,0.00001952382,0.0005788991],"category_scores_gemma":[0.00001236169,0.00008989242,0.0002894033,0.00004941507,0.00008396286,0.0007905284,0.000001003306,0.0001345215,0.000006884577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001112152,"about_ca_system_score_gemma":0.00001128657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008100418,"about_ca_topic_score_gemma":0.0001252892,"domain_scores_codex":[0.9991698,0.00006715088,0.0002940227,0.0001157242,0.0001606388,0.0001926437],"domain_scores_gemma":[0.9994805,0.0001356245,0.0001442059,0.00007108004,0.000107564,0.00006103566],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007096583,0.00005723435,0.00001591389,0.00001096448,0.0006715191,0.000002078877,0.00424169,0.0001195034,0.0003336005,0.02311966,0.0008216981,0.9705352],"study_design_scores_gemma":[0.0003503832,0.0001790668,0.0003024116,0.000006734286,0.001427003,0.00001931776,0.0002746169,0.0001020858,0.0000629251,0.0304062,0.9667464,0.000122789],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.06515705,0.5971294,0.2282923,0.03406973,0.003215874,0.0009322077,0.0001174447,0.0002820627,0.07080396],"genre_scores_gemma":[0.9597983,0.02093298,0.01370475,0.001042859,0.002664968,0.00001021869,0.00001663332,0.00003282112,0.0017965],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9704124,"threshold_uncertainty_score":0.6559038,"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."}}