{"id":"W2176008306","doi":"10.1016/j.cie.2015.11.011","title":"Green supplier development program selection using NGT and VIKOR under fuzzy environment","year":2015,"lang":"en","type":"article","venue":"Computers & Industrial Engineering","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":286,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Ranking (information retrieval); Fuzzy logic; Supplier evaluation; Supply chain; Context (archaeology); VIKOR method; Nominal group technique; Computer science; Supply chain management; Selection (genetic algorithm); Operations research; Process management; Operations management; Business; Knowledge management; Engineering; Marketing; 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":[0.001156643,0.0005103365,0.0008598476,0.002210644,0.0006936977,0.001051383,0.0006782557,0.0005338671,0.001629963],"category_scores_gemma":[0.002334747,0.0002553772,0.001001976,0.001646776,0.0003221747,0.0008836524,0.0005127682,0.0003066197,0.000129894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001003752,"about_ca_system_score_gemma":0.001364839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006423722,"about_ca_topic_score_gemma":0.005343013,"domain_scores_codex":[0.9990331,0.0003103693,0.00004470244,0.0001190856,0.0003735957,0.0001191986],"domain_scores_gemma":[0.9991056,0.0004959423,0.00009151395,0.00003282876,0.0002295845,0.0000444951],"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":[0.0004192092,0.0001997555,0.006973085,0.0003191307,0.000134341,0.0002877867,0.0001560404,0.8068205,0.006868311,0.009992294,0.001386714,0.1664429],"study_design_scores_gemma":[0.00001540305,0.00007596353,0.001130736,0.00001085995,0.00003633498,0.00004978732,0.00005474903,0.9953768,0.001294042,0.001578394,0.0003658064,0.00001104563],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3986514,0.0004482609,0.5849546,0.0002788733,0.00006005076,0.0002226497,0.0001950475,0.0004227567,0.01476642],"genre_scores_gemma":[0.9055039,0.0001518236,0.09171304,0.00002881165,0.00001484144,0.00009905541,0.0001159347,0.00002129062,0.002351337],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006423722,"threshold_uncertainty_score":0.01277262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2914001476932958,"score_gpt":0.3637968851658938,"score_spread":0.072396737472598,"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."}}