{"id":"W2092890259","doi":"10.1016/j.eswa.2010.08.054","title":"Design and implementation of GEmA: A generic emotional agent","year":2010,"lang":"en","type":"article","venue":"Expert Systems with Applications","topic":"Social Robot Interaction and HRI","field":"Psychology","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Java; Rationality; Morality; Intelligent agent; Artificial intelligence; Software; Emotional behavior; Software agent; Software engineering; Programming language; Human–computer interaction; Machine learning; Psychology","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":[],"consensus_categories":[],"category_scores_codex":[0.00009709292,0.00007119777,0.0001003612,0.00005687583,0.0001027955,0.00001785258,0.00006181307,0.00004919852,0.0006384801],"category_scores_gemma":[0.000001876949,0.00006117306,0.00001805245,0.0001144012,0.00004662779,0.00004079593,0.000008582091,0.00006973816,0.00007443012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001512623,"about_ca_system_score_gemma":0.00002993623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005804457,"about_ca_topic_score_gemma":0.00004662669,"domain_scores_codex":[0.9993948,0.00004507125,0.0001934991,0.0001680169,0.0001021019,0.00009647693],"domain_scores_gemma":[0.999476,0.00006349249,0.000131303,0.0001878038,0.00008591382,0.00005554274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001683865,0.000937594,0.01811775,0.00008882671,0.0006422429,0.000004627136,0.04472557,0.0002329959,0.177968,0.6306283,0.07468596,0.05179974],"study_design_scores_gemma":[0.004289562,0.0005386125,0.1799294,0.00005588008,0.0001040991,0.000511237,0.06101201,0.001200414,0.005083604,0.0005521523,0.74582,0.0009029839],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09022498,0.0004749376,0.9000703,0.000673871,0.0008815642,0.002255543,0.0000174061,0.0001007034,0.00530073],"genre_scores_gemma":[0.9902893,0.000008498992,0.005989387,0.00009640725,0.000254268,0.002622197,0.00001967028,0.00001403675,0.0007062695],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9000643,"threshold_uncertainty_score":0.6990909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04554601365028967,"score_gpt":0.3863390342902817,"score_spread":0.340793020639992,"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."}}