{"id":"W4237236521","doi":"10.1007/10719619","title":"Intelligent Agents VI. Agent Theories, Architectures, and Languages","year":2000,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Intelligent agent; Programming language; Agent architecture; Artificial intelligence; Cognitive science","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":[0.0003906957,0.0009759282,0.0008079454,0.001082,0.0007198742,0.003454259,0.0009270895,0.001292197,0.01243976],"category_scores_gemma":[0.001033192,0.0005818224,0.0004481959,0.001412079,0.001754776,0.004150146,0.001071308,0.002214192,0.006397162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001112574,"about_ca_system_score_gemma":0.001015621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001067478,"about_ca_topic_score_gemma":0.001307116,"domain_scores_codex":[0.9997376,0.00006560772,0.00002633483,0.00004168368,0.000103832,0.00002499003],"domain_scores_gemma":[0.9997005,0.0001492632,0.0000277091,0.00003448032,0.00005558389,0.00003246979],"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":[0.00002905409,0.00002680749,0.0001847237,0.0005602056,0.00002935987,0.00009165011,0.0005914372,0.002101325,0.0007980546,0.794524,0.07859384,0.1224696],"study_design_scores_gemma":[0.000009834892,0.00001538071,0.0001887114,0.0004898487,0.00002269749,0.0002007494,0.0002532738,0.002768952,0.0004817832,0.4508943,0.5446633,0.00001119084],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.003572038,0.2607201,0.1396077,0.008265485,0.002948928,0.0001319182,0.0003360798,0.0007281299,0.5836896],"genre_scores_gemma":[0.1523061,0.1710577,0.1375616,0.003739606,0.003049195,0.0006582201,0.001040639,0.0005541253,0.5300328],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.01243976,"threshold_uncertainty_score":0.04161513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01489579374231335,"score_gpt":0.2637559998466782,"score_spread":0.2488602061043649,"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."}}