{"id":"W4247995482","doi":"10.24124/2008/bpgub543","title":"Development of fuzzy multi-criteria decision analysis approach for contaminated site management.","year":2008,"lang":"en","type":"dissertation","venue":"","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Heritage; University of Northern British Columbia; Library and Archives Canada","funders":"University of Northern British Columbia","keywords":"Multiple-criteria decision analysis; Fuzzy logic; Selection (genetic algorithm); Site selection; Process (computing); Fuzzy set; Task (project management); Management science; Decision analysis; Risk analysis (engineering); Decision support system; Computer science; Government (linguistics); Operations research; Set (abstract data type); Engineering; Data mining; Systems engineering; Business; Artificial intelligence; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002978654,0.000914344,0.0007722861,0.002215916,0.001032816,0.001669257,0.001021599,0.001050418,0.003110231],"category_scores_gemma":[0.003667108,0.0003675274,0.001549327,0.00133759,0.0005689515,0.001013763,0.0009929745,0.001456078,0.0004009115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002039865,"about_ca_system_score_gemma":0.003331062,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005224735,"about_ca_topic_score_gemma":0.008111996,"domain_scores_codex":[0.9984632,0.0006554965,0.00009119503,0.0001269611,0.0006071983,0.00005610257],"domain_scores_gemma":[0.9991359,0.0004063345,0.00006099515,0.00002402898,0.0003330081,0.00003974314],"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":[0.00008366904,0.0002307882,0.001327529,0.0009865051,0.0002695514,0.0005008107,0.000946717,0.4791065,0.009362356,0.1230326,0.005655845,0.378497],"study_design_scores_gemma":[0.00004342418,0.0001480789,0.0005849159,0.0002577296,0.00007131499,0.0001714071,0.0002845424,0.9216551,0.003338949,0.05223283,0.02115174,0.00006004688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005357514,0.000819711,0.9854307,0.000399363,0.00008862774,0.0004134545,0.00010139,0.00007474337,0.007314569],"genre_scores_gemma":[0.06056448,0.0005893674,0.9364932,0.00007179643,0.00002090224,0.00043674,0.00009332201,0.00001331885,0.001716845],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005224735,"threshold_uncertainty_score":0.01575279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1620029832105565,"score_gpt":0.4425473250152705,"score_spread":0.280544341804714,"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."}}