{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009405956,0.0006388449,0.0005523594,0.0003388399,0.0003816769,0.001299361,0.002855956,0.001320797,0.008426075],"category_scores_gemma":[0.002096943,0.0005427886,0.0005087779,0.0001268627,0.0005687645,0.0009363979,0.001687699,0.001295295,0.003599416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003922023,"about_ca_system_score_gemma":0.0008439369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007136699,"about_ca_topic_score_gemma":0.0007374602,"domain_scores_codex":[0.9994965,0.000106001,0.00005018933,0.0001189366,0.0001413197,0.00008706412],"domain_scores_gemma":[0.9994784,0.0001049423,0.00004608801,0.0001240632,0.0001260373,0.0001204016],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002121579,0.001958203,0.007539957,0.002085184,0.0004278856,0.001082354,0.002186891,0.06649672,0.3136783,0.05198017,0.02957329,0.5208695],"study_design_scores_gemma":[0.0006886435,0.001371875,0.003743231,0.0001569801,0.0003356249,0.001082187,0.0003859164,0.5720158,0.2004878,0.009982755,0.2095696,0.0001796039],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03179463,0.0001627984,0.9312425,0.0002877116,0.0002139596,0.001534786,0.0003014346,0.02572729,0.008734936],"genre_scores_gemma":[0.2521327,0.0001416857,0.7290186,0.0004451229,0.00003604253,0.00156687,0.0007654031,0.00220463,0.01368899],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008426075,"threshold_uncertainty_score":0.02818799,"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."}}