{"id":"W291277668","doi":"","title":"A Fuzzy Logic Computational Model for Emotion Regulation Based on Gross","year":2013,"lang":"en","type":"article","venue":"The Florida AI Research Society","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Fuzzy logic; Consistency (knowledge bases); Computer science; Artificial intelligence; Control (management); Machine learning","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":[0.001805195,0.000119161,0.0001107478,0.00007089984,0.0006475545,0.0001007708,0.0001962662,0.0001640601,0.0006701596],"category_scores_gemma":[0.0001002396,0.00008658549,0.0002092409,0.0002989062,0.0002094999,0.0001370409,0.00003236637,0.0004311582,0.0008109327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001337052,"about_ca_system_score_gemma":0.00008209836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004691974,"about_ca_topic_score_gemma":0.000003047035,"domain_scores_codex":[0.9981205,0.0003226661,0.000207658,0.0003225489,0.0005897516,0.0004368067],"domain_scores_gemma":[0.9982086,0.0005926471,0.00005756679,0.0002987968,0.0007540843,0.00008823942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002503067,0.000491495,0.0001035231,0.00007895329,0.00009420011,5.539359e-7,0.006301064,0.1773937,0.0007385052,0.1460322,0.6528657,0.01564977],"study_design_scores_gemma":[0.000932581,0.000154905,0.006246838,0.00001534142,0.000005953082,0.000001499366,0.0004832978,0.755798,0.00002948367,0.2359249,0.0003246844,0.00008255956],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1902167,0.00004180154,0.7205049,0.05634148,0.001198714,0.004707444,0.0001187922,0.0003049413,0.02656525],"genre_scores_gemma":[0.9850985,0.000004172306,0.003981293,0.00344115,0.000420813,0.0007087518,0.0003052878,0.00002688606,0.006013161],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7948818,"threshold_uncertainty_score":0.999967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1690615925025254,"score_gpt":0.4292259672565886,"score_spread":0.2601643747540632,"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."}}