{"id":"W1974685448","doi":"10.1016/j.cogsys.2005.03.002","title":"Agent communication pragmatics: the cognitive coherence approach","year":2005,"lang":"en","type":"article","venue":"Cognitive Systems Research","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"","keywords":"Pragmatics; Computer science; Semantics (computer science); Coherence (philosophical gambling strategy); Toolbox; Cognitive science; Syntax; Cognition; Artificial intelligence; Psychology; Linguistics; Programming language","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0135738,0.00107926,0.001628795,0.003322335,0.003678191,0.01149683,0.002840195,0.005043911,0.007995102],"category_scores_gemma":[0.04501947,0.001415549,0.001564853,0.002796435,0.01529461,0.0274028,0.005855068,0.005485218,0.0008576245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004155212,"about_ca_system_score_gemma":0.003890881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003910856,"about_ca_topic_score_gemma":0.002185696,"domain_scores_codex":[0.9862739,0.009154898,0.0006633276,0.001141813,0.00218445,0.0005814586],"domain_scores_gemma":[0.9706694,0.02260831,0.001501792,0.002254392,0.00218256,0.0007834409],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002829589,0.00001803192,0.000179126,0.0001063223,0.00003247461,0.00005358347,0.00227402,0.001246695,0.0001451063,0.987961,0.0007612185,0.007194049],"study_design_scores_gemma":[0.00002655704,0.00001220182,0.0001593573,0.00004351432,0.00002324212,0.00004561928,0.0005083652,0.004262211,0.00008395713,0.9896938,0.005127351,0.00001384143],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02303739,0.008396639,0.8085098,0.03156309,0.0007245309,0.0002250674,0.0001973468,0.0002462822,0.1270998],"genre_scores_gemma":[0.8535734,0.002534205,0.1356185,0.001399344,0.0009752562,0.0004654913,0.000176985,0.0002003155,0.005056572],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0135738,"threshold_uncertainty_score":0.07178593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1632641581410741,"score_gpt":0.3959595245002275,"score_spread":0.2326953663591534,"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."}}