{"id":"W2041621149","doi":"10.1016/j.ins.2013.04.004","title":"Generalized fuzzy linear programming for decision making under uncertainty: Feasibility of fuzzy solutions and solving approach","year":2013,"lang":"en","type":"article","venue":"Information Sciences","topic":"Water resources management and optimization","field":"Engineering","cited_by":63,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Mathematical optimization; Mathematics; Fuzzy logic; Fuzzy number; Membership function; Fuzzy set operations; Robustness (evolution); Linear programming; Defuzzification; Discretization; Fuzzy classification; Interval (graph theory); Fuzzy set; Computer science; Algorithm; Artificial intelligence","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":[0.0004977263,0.00007851987,0.0000961499,0.00017292,0.0002215749,0.0002200713,0.0001237507,0.00003618498,0.000007159952],"category_scores_gemma":[0.00006777677,0.00006421503,0.00003020976,0.000289419,0.00009327786,0.001609372,0.00004975228,0.00003230288,0.000003634768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002749415,"about_ca_system_score_gemma":0.00000911644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003017192,"about_ca_topic_score_gemma":0.000006823019,"domain_scores_codex":[0.999225,0.000009977884,0.000304148,0.00008543533,0.0001903828,0.000185095],"domain_scores_gemma":[0.9996485,0.0000634863,0.00008164061,0.00008536345,0.00009343503,0.00002755724],"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":[0.000003489539,0.000005734119,0.0006006032,0.00008623808,0.000005883026,4.20759e-9,0.0008593901,0.9554251,0.00003474402,0.002040034,0.0001414247,0.04079739],"study_design_scores_gemma":[0.0001924103,0.00002150794,0.001314596,0.00002988269,0.00000673041,5.005996e-7,0.0009385368,0.9944332,0.0000224288,0.002460995,0.0004923896,0.00008681663],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2922728,0.00005417479,0.7040528,0.00004221386,0.00008393135,0.0006540302,0.000002957637,0.0001001108,0.00273697],"genre_scores_gemma":[0.8456138,0.000009762373,0.1542595,0.00002730468,0.00001684658,0.00004946472,0.00001272294,0.000003202427,0.000007412802],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.553341,"threshold_uncertainty_score":0.2618613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05117451207945224,"score_gpt":0.2797867604101935,"score_spread":0.2286122483307413,"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."}}