{"id":"W2610928249","doi":"10.5430/wjel.v7n1p35","title":"Textual Function of Presupposition in Business Letter Discourse","year":2017,"lang":"en","type":"article","venue":"World Journal of English Language","topic":"Lexicography and Language Studies","field":"Arts and Humanities","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Presupposition; Linguistics; Sentence; Computer science; Utterance; Theme (computing); Function (biology); Nominalization; Noun; Philosophy; World Wide Web","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":[0.002213637,0.0002850161,0.0002082319,0.001128564,0.001983464,0.003398188,0.0006914921,0.0008279174,0.003813526],"category_scores_gemma":[0.01172811,0.0001768716,0.0001952958,0.001395426,0.004489388,0.005406664,0.0015093,0.000696602,0.0003496069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002542896,"about_ca_system_score_gemma":0.001214505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001230948,"about_ca_topic_score_gemma":0.0009739932,"domain_scores_codex":[0.9967939,0.002228474,0.0001406454,0.0002308403,0.0004864278,0.0001195545],"domain_scores_gemma":[0.9871624,0.01063683,0.0006867684,0.0005885998,0.0007789567,0.0001464585],"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":[0.0007811438,0.0001364723,0.008752818,0.0008635366,0.00002504494,0.0021249,0.4262987,0.001088655,0.03294676,0.4404446,0.001155109,0.08538226],"study_design_scores_gemma":[0.0001173945,0.000526481,0.05006408,0.001000593,0.0001219966,0.001926258,0.4850883,0.01877507,0.09060948,0.2163102,0.1352609,0.0001992191],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8452878,0.0008831187,0.05343705,0.001912573,0.00006792757,0.0001337064,0.0003075802,0.0002262616,0.097744],"genre_scores_gemma":[0.9957175,0.0001021685,0.002478782,0.00002795376,0.0000088883,0.00002933515,0.00005103496,0.00001273563,0.001571582],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003813526,"threshold_uncertainty_score":0.01845008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0127356853394691,"score_gpt":0.2465127291164459,"score_spread":0.2337770437769768,"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."}}