{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001684871,0.0002839191,0.0003652576,0.0004528739,0.0001320842,0.0004853912,0.0004240324,0.000211685,0.00003914008],"category_scores_gemma":[0.0003012918,0.0002567349,0.00005908439,0.0005213668,0.00004132461,0.0003524616,0.0003556272,0.0003129418,0.0000557435],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003677316,"about_ca_system_score_gemma":0.0001380877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002676779,"about_ca_topic_score_gemma":0.00000215088,"domain_scores_codex":[0.9969078,0.00008660826,0.0007522671,0.0006324864,0.001189756,0.0004310393],"domain_scores_gemma":[0.9987192,0.0003403586,0.0001667989,0.0003149668,0.00009417043,0.0003645263],"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":[0.0000494553,0.00006190535,0.001284512,0.00000373147,0.0000492839,0.0000134771,0.0005056012,0.39685,0.003513197,0.0001217548,0.0008735718,0.5966735],"study_design_scores_gemma":[0.002230257,0.0001257842,0.002533896,0.00007569072,0.00002165533,0.00006199085,0.0001799189,0.8555366,0.001467301,0.0004482768,0.1367386,0.0005800566],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5685316,0.00005715966,0.4289017,0.0001376913,0.001653649,0.0005091827,0.000002268709,0.0001616399,0.00004505578],"genre_scores_gemma":[0.7395751,0.000001148296,0.2592589,0.00006456472,0.0008560126,0.00002760694,0.00000553393,0.00004744966,0.00016362],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5960935,"threshold_uncertainty_score":0.9999885,"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."}}