{"id":"W2019495791","doi":"10.1504/ijleg.2012.050208","title":"Integrating fuzzy Delphi with graph theory and matrix methods for evaluation of hazardous industrial waste transportation firm","year":2012,"lang":"en","type":"article","venue":"International Journal of Logistics Economics and Globalisation","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Hazardous waste; Delphi method; Fuzzy logic; Delphi; Automotive industry; Computer science; Risk analysis (engineering); Business; Operations research; Engineering; Waste management; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01327343,0.001084636,0.0007281659,0.00485106,0.002020702,0.00269596,0.0008984528,0.0007349215,0.002621112],"category_scores_gemma":[0.0111353,0.0005940124,0.0009300745,0.00337768,0.001407775,0.002130954,0.002674421,0.0009675638,0.0001429332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004575028,"about_ca_system_score_gemma":0.006019583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007331883,"about_ca_topic_score_gemma":0.01161195,"domain_scores_codex":[0.9792796,0.01686688,0.0005329662,0.0003433821,0.002471151,0.0005060418],"domain_scores_gemma":[0.9931943,0.004852315,0.0003245329,0.0001682537,0.001284043,0.0001764667],"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":[0.0006722651,0.0007739664,0.0106096,0.002751521,0.0004850338,0.0007966674,0.01704346,0.2676521,0.008127925,0.2631921,0.005371306,0.4225241],"study_design_scores_gemma":[0.0002355508,0.001257556,0.008996652,0.0008866379,0.0002624773,0.0004013826,0.03044725,0.738542,0.006478179,0.1939106,0.01822794,0.0003537632],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.204965,0.00123552,0.7466124,0.002313226,0.0001219754,0.003547969,0.0002023982,0.0001033524,0.04089813],"genre_scores_gemma":[0.6896226,0.0006996773,0.3063911,0.0001272847,0.00002001123,0.001547711,0.00005703187,0.000009969264,0.001524689],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01327343,"threshold_uncertainty_score":0.07019746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2379355142873513,"score_gpt":0.4854427793678455,"score_spread":0.2475072650804941,"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."}}