{"id":"W2145029849","doi":"10.1109/cec.2010.5586121","title":"Artificial emotional intelligence under ethical constraints in formulating social agent behaviour","year":2010,"lang":"en","type":"article","venue":"","topic":"Scheduling and Timetabling Solutions","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Reputation; Multi-agent system; Convergence (economics); Graph; Process (computing); Artificial intelligence; Management science; Knowledge management; Theoretical computer science; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004328119,0.0001143036,0.0001891903,0.0002700344,0.0003731686,0.0002324633,0.0003915885,0.000340597,0.004633378],"category_scores_gemma":[0.003695731,0.00009186834,0.0001306561,0.0006852498,0.0005073128,0.0001324405,0.00009658388,0.001193441,0.0007039422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002912187,"about_ca_system_score_gemma":0.0002008058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008268687,"about_ca_topic_score_gemma":0.000985376,"domain_scores_codex":[0.9973224,0.0001279576,0.0007422962,0.000403334,0.001046255,0.0003577977],"domain_scores_gemma":[0.9982169,0.001081739,0.0001155495,0.0002170645,0.0002523211,0.0001164656],"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":[0.00001149203,0.0001861996,0.02329239,7.535482e-7,0.000007115709,0.000006847885,0.0007823524,0.001510047,0.002601849,0.8972567,0.0003867268,0.07395751],"study_design_scores_gemma":[0.0001396657,0.00002482475,0.2206016,0.000008932876,0.00001038396,0.00002560288,0.002317817,0.03721731,0.00173505,0.7374792,0.0001639964,0.0002756676],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8640354,0.000001986593,0.1232127,0.006958182,0.0008939461,0.000090389,0.000009105919,0.00005582474,0.004742504],"genre_scores_gemma":[0.9864545,1.838602e-7,0.0124806,0.0005118573,0.0001864417,0.000005021338,0.00000421653,0.000006644753,0.0003505772],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1973092,"threshold_uncertainty_score":0.9962765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2628448554260898,"score_gpt":0.4637222080975839,"score_spread":0.2008773526714941,"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."}}