{"id":"W2087462978","doi":"10.5430/air.v2n1p55","title":"Yager ranking index in fuzzy bilevel optimization","year":2012,"lang":"en","type":"article","venue":"Artificial Intelligence Research","topic":"Fuzzy Systems and Optimization","field":"Mathematics","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bilevel optimization; Mathematical optimization; Ranking (information retrieval); Fuzzy logic; Optimization problem; Selection (genetic algorithm); Mathematics; Computer science; Pessimism; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005092075,0.0001375254,0.000210401,0.0005854308,0.000209594,0.0001196871,0.0002627509,0.0001735743,0.0004328441],"category_scores_gemma":[0.001794161,0.0001274409,0.00005190373,0.001406247,0.0001158323,0.0004884199,0.0001154549,0.0004364842,0.0002005833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001837571,"about_ca_system_score_gemma":0.00007856148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000348085,"about_ca_topic_score_gemma":0.0001743248,"domain_scores_codex":[0.9970998,0.0004401849,0.0006012008,0.0002674031,0.0007738777,0.0008175444],"domain_scores_gemma":[0.9982746,0.0008184901,0.00008005921,0.0003478067,0.0003364844,0.0001425277],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002038759,0.001338645,0.02077928,0.0002855113,0.00003917388,0.00001964395,0.01242256,0.1814033,0.001558428,0.6835067,0.001419566,0.09702323],"study_design_scores_gemma":[0.000128339,0.0001006417,0.0008302566,0.0003270097,0.00001019116,0.00001206227,0.00601312,0.5356324,0.01540507,0.4404124,0.0005551094,0.0005733287],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1625382,0.0003975855,0.8127123,0.0006759826,0.0008609707,0.001578076,0.000008331654,0.0001548719,0.0210737],"genre_scores_gemma":[0.9852022,0.00004944215,0.01390172,0.00001714816,0.0003928344,0.00007629773,0.000006938659,0.00003675615,0.0003166928],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8226639,"threshold_uncertainty_score":0.5196888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3967703050662592,"score_gpt":0.4747694166049607,"score_spread":0.07799911153870154,"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."}}