{"id":"W1967275664","doi":"10.5539/ells.v3n3p16","title":"Pragmatics Encoded and Decoded Message","year":2013,"lang":"en","type":"article","venue":"English Language and Literature Studies","topic":"Language, Discourse, Communication Strategies","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pragmatics; Presupposition; Computer science; Feature (linguistics); Linguistics; Inference; Field (mathematics); Subject (documents); Logical consequence; Order (exchange); Natural language processing; Artificial intelligence; Philosophy; Mathematics; 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":[0.001552559,0.0004750621,0.0003618699,0.001088911,0.001188911,0.005643677,0.0007183378,0.001399452,0.01364399],"category_scores_gemma":[0.01057955,0.0004546163,0.0004120032,0.0007901437,0.002519477,0.00617162,0.002425762,0.001876941,0.003323323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001805145,"about_ca_system_score_gemma":0.00159965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003415036,"about_ca_topic_score_gemma":0.00162743,"domain_scores_codex":[0.9981015,0.0007099031,0.0001368407,0.0003269784,0.0005538457,0.0001708991],"domain_scores_gemma":[0.9968811,0.001073726,0.0001982043,0.000630345,0.001106182,0.000110462],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002158042,0.00003615283,0.001441686,0.0004686399,0.00003363146,0.001121253,0.03459714,0.001191674,0.02890301,0.8485137,0.005647766,0.07782971],"study_design_scores_gemma":[0.00008396476,0.0002375042,0.009054942,0.0006841566,0.0002154322,0.002151991,0.02085392,0.02890476,0.03334737,0.5736629,0.3305655,0.0002374829],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1104126,0.001733257,0.4555492,0.01021093,0.001521984,0.0004461961,0.003030614,0.002321556,0.4147736],"genre_scores_gemma":[0.8796114,0.0007911475,0.08168548,0.0004995235,0.0002791209,0.0001483153,0.001243532,0.0007568061,0.03498458],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01364399,"threshold_uncertainty_score":0.04564369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01632353516157749,"score_gpt":0.2704674245842403,"score_spread":0.2541438894226628,"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."}}