{"id":"W2395680703","doi":"","title":"Emotionally Responsive General Artificial Agent Simulation","year":2011,"lang":"en","type":"article","venue":"The Florida AI Research Society","topic":"Social Robot Interaction and HRI","field":"Psychology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Process (computing); Artificial intelligence; Multi-agent system; Event (particle physics); Human–computer interaction; 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":[0.000264691,0.0004098637,0.0003941055,0.0002239282,0.0003372896,0.0007413342,0.001002518,0.0009885479,0.004566792],"category_scores_gemma":[0.001307192,0.0001838645,0.0004928955,0.0001860227,0.0006270643,0.0005948333,0.001101293,0.0006502145,0.0004041805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005534943,"about_ca_system_score_gemma":0.0004638517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002801553,"about_ca_topic_score_gemma":0.001806299,"domain_scores_codex":[0.9998511,0.00006893712,0.000005567437,0.00002249528,0.00002868068,0.00002312404],"domain_scores_gemma":[0.9997407,0.0001391437,0.00002600151,0.00003230902,0.00003919108,0.0000227106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003552383,0.00002733318,0.000209452,0.00002833492,0.00001064427,0.00006423425,0.0000798015,0.9774978,0.00206412,0.01716324,0.0002814968,0.002537998],"study_design_scores_gemma":[0.00001061677,0.0000125937,0.00005948669,0.000002303946,0.000002213027,0.000008154687,0.00001263752,0.9951142,0.0002343864,0.004015072,0.0005250052,0.000003222657],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2594585,0.0002481812,0.6747647,0.0006765943,0.0001155229,0.0003020851,0.0003317174,0.0008702602,0.06323241],"genre_scores_gemma":[0.9288485,0.0001643394,0.0605957,0.00008896599,0.0000126933,0.0003162979,0.000111553,0.00005872381,0.00980313],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004566792,"threshold_uncertainty_score":0.01527745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4142860662189123,"score_gpt":0.5177621775213253,"score_spread":0.103476111302413,"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."}}