{"id":"W2410695560","doi":"10.5539/ells.v6n2p193","title":"A Pragmatic Analysis of Humor Words in English Advertisements","year":2016,"lang":"en","type":"article","venue":"English Language and Literature Studies","topic":"Language, Metaphor, and Cognition","field":"Psychology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cooperative principle; Linguistics; Newspaper; Grammar; Presupposition; Deixis; Situational ethics; Pragmatics; Vocabulary; Perspective (graphical); Rhetoric; Humor research; Psychology; Speech act; Euphemism; Target audience; Focus (optics); Politeness; Advertising; Computer science; Grice; Artificial intelligence","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":[0.0003365429,0.0001872709,0.0005043058,0.000476236,0.00004031798,0.00002631162,0.00009925239,0.00009856767,0.0003634878],"category_scores_gemma":[0.0008019223,0.0001150909,0.0001220738,0.0009915829,0.00008493763,0.0001700125,0.00005771641,0.0001303894,0.000003409743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002074303,"about_ca_system_score_gemma":0.000005880491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002620805,"about_ca_topic_score_gemma":0.0001811419,"domain_scores_codex":[0.9987108,0.0001913667,0.0003487532,0.0003308516,0.0001646015,0.0002536718],"domain_scores_gemma":[0.9990698,0.0002549784,0.0001221544,0.0002791121,0.000227824,0.00004611375],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00007872362,0.0001340815,0.01094731,0.00008056933,0.0022196,0.000170909,0.9688834,2.330342e-7,0.0003396786,0.001410714,0.0008145557,0.01492026],"study_design_scores_gemma":[0.004479005,0.0002619334,0.07203574,0.00123484,0.002199521,0.000004531996,0.91412,0.000004953881,0.0005910398,0.000555615,0.003890964,0.0006218551],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9496911,0.03947526,0.00002385751,0.00003459691,0.0005405097,0.0001776901,0.0001361672,0.00005855474,0.009862226],"genre_scores_gemma":[0.9963687,0.000405939,0.00008298113,0.0001053211,0.0003141597,0.0000776778,0.00005142798,0.00001302305,0.002580753],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06108844,"threshold_uncertainty_score":0.469327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008181424514588328,"score_gpt":0.2924959062832331,"score_spread":0.2843144817686448,"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."}}