{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000148732,0.0002122775,0.0002762516,0.0000771224,0.0003652162,0.0008982432,0.0001335745,0.00005330937,0.0003379125],"category_scores_gemma":[0.0002621176,0.0001456539,0.00003642619,0.00005106759,0.0003727027,0.0006900182,0.0001571766,0.0002207076,0.00001088756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008532564,"about_ca_system_score_gemma":0.000009228152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005060003,"about_ca_topic_score_gemma":0.0003009728,"domain_scores_codex":[0.9991534,0.00009154471,0.0002160116,0.0002068229,0.0001260493,0.0002062249],"domain_scores_gemma":[0.9990252,0.0002211236,0.00008291215,0.0003105779,0.0002992784,0.0000608583],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.000003042427,0.00002122424,0.00006048405,0.0001031745,0.0001162254,0.00001428753,0.9039321,1.212601e-7,0.00004875007,0.08582781,0.007981312,0.001891461],"study_design_scores_gemma":[0.0003887838,0.00004309104,0.0001437993,0.0001934449,0.00005155348,0.000006862793,0.9636297,0.0000139771,0.00009033784,0.003613109,0.03155588,0.0002694491],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8111239,0.1028007,0.000003434821,0.0005980497,0.0002985125,0.0002922824,0.00004695754,0.0001803866,0.08465578],"genre_scores_gemma":[0.9883819,0.001595934,0.0005438712,0.0003098298,0.0006250144,0.00008001791,0.00004219402,0.00001975092,0.008401508],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.177258,"threshold_uncertainty_score":0.866178,"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."}}