{"id":"W3202375536","doi":"","title":"Development of a fuzzy multi-criteria decision support system for municipal solid waste management.","year":2001,"lang":"en","type":"dissertation","venue":"oURspace (University of Regina)","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Solid waste management; Fuzzy logic; Decision support system; Municipal solid waste; Waste management; Engineering; Computer science; Business; Environmental planning; Operations research; Environmental science; Risk analysis (engineering); Data mining; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007747089,0.0003437111,0.0004620177,0.0003724459,0.0004813089,0.001045635,0.0008290629,0.0007962456,0.004211926],"category_scores_gemma":[0.001503862,0.0003216042,0.0004688578,0.0002493392,0.0001346323,0.0008206227,0.000491735,0.0006733346,0.001190651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003866405,"about_ca_system_score_gemma":0.0009891918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00321587,"about_ca_topic_score_gemma":0.003726063,"domain_scores_codex":[0.9997575,0.00004528817,0.00002358184,0.00004041099,0.0001144244,0.00001887065],"domain_scores_gemma":[0.9997072,0.00007377488,0.00002021164,0.00001884719,0.0001458315,0.00003400527],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006119717,0.0004180726,0.002941532,0.0008069338,0.0002534394,0.0009118052,0.0005708111,0.1048949,0.07060879,0.008883255,0.01290158,0.7961969],"study_design_scores_gemma":[0.0002047458,0.0004368994,0.002208686,0.0001533566,0.0001502737,0.0003496062,0.0002090989,0.9115241,0.04330228,0.00415331,0.03724799,0.0000595896],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.05404903,0.0008054891,0.9296313,0.0009957325,0.0002437717,0.0009266969,0.0005055876,0.006989847,0.005852622],"genre_scores_gemma":[0.2435572,0.0005219103,0.7471485,0.0002254564,0.00004186353,0.0005610543,0.0006448612,0.0001146172,0.007184444],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.004211926,"threshold_uncertainty_score":0.0140903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08642081273625737,"score_gpt":0.3670503618942422,"score_spread":0.2806295491579848,"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."}}