{"id":"W2501702276","doi":"10.1007/978-3-319-34111-8_10","title":"Fuzzy Computational Model for Emotions Originated in Workplace Events","year":2016,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Emotions and Moral Behavior","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Affect (linguistics); Computer science; Set (abstract data type); Fuzzy logic; Test (biology); Control (management); Fuzzy set; Artificial intelligence; Performance appraisal; Operations research; Psychology; Management; Mathematics; 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":[0.0004069438,0.0003885325,0.0005409435,0.0005208461,0.0004983585,0.001294303,0.001644528,0.001002997,0.007401633],"category_scores_gemma":[0.001314022,0.0002215813,0.000781553,0.0004649983,0.0005184999,0.001313103,0.0004754802,0.001156584,0.0006030682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001076009,"about_ca_system_score_gemma":0.0006235624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009125923,"about_ca_topic_score_gemma":0.007477459,"domain_scores_codex":[0.9998533,0.00004033027,0.000007645021,0.00003037798,0.00004047673,0.00002789805],"domain_scores_gemma":[0.9997048,0.0001848711,0.00001802205,0.0000175307,0.00005493687,0.00001985432],"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":[0.00008368886,0.00009359666,0.0008870368,0.0001110687,0.00007045017,0.000191163,0.0002666936,0.5561043,0.002184171,0.4071723,0.002669263,0.03016625],"study_design_scores_gemma":[0.000004826602,0.000007532431,0.0001583671,0.000007152534,0.000007674625,0.00001632362,0.0000211635,0.9594742,0.00009336678,0.03974993,0.0004538891,0.000005522366],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07513006,0.001045021,0.8902797,0.001255652,0.0002030775,0.00005652963,0.000367765,0.0002049754,0.03145724],"genre_scores_gemma":[0.908289,0.000669371,0.07123316,0.0001537165,0.0001190614,0.0001541425,0.0003240584,0.00004368707,0.01901382],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009125923,"threshold_uncertainty_score":0.02476096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04309470697662886,"score_gpt":0.3343435497086847,"score_spread":0.2912488427320559,"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."}}