{"id":"W2809415840","doi":"10.1016/j.spc.2018.05.008","title":"An integrated fuzzy MCDM approach to improve sustainable consumption and production trends in supply chain","year":2018,"lang":"en","type":"article","venue":"Sustainable Production and Consumption","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Supply chain; Process management; Production (economics); Dimension (graph theory); Key (lock); Fuzzy logic; Consumption (sociology); Process (computing); Rank (graph theory); Business; Supply chain management; Supply chain network; Industrial organization; Computer science; Risk analysis (engineering); Marketing; Economics; Microeconomics; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002439232,0.0005023225,0.0004045054,0.002907487,0.0007186431,0.0008920627,0.0002252679,0.0001926682,0.0001200856],"category_scores_gemma":[0.0006047516,0.0005226585,0.00004602984,0.00210325,0.0004044496,0.004075826,0.0003362084,0.0003309481,0.00006006672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005772943,"about_ca_system_score_gemma":0.00006221882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002597708,"about_ca_topic_score_gemma":0.000323722,"domain_scores_codex":[0.9961247,0.0001199728,0.0005692019,0.00160939,0.0003988869,0.001177881],"domain_scores_gemma":[0.997789,0.00001484566,0.0002659965,0.0006601006,0.001175556,0.00009451102],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003875198,0.002727723,0.1887694,0.01227897,0.0002144455,0.0001681978,0.007583689,0.002248569,0.004709437,0.3762513,0.02610637,0.3750667],"study_design_scores_gemma":[0.005796876,0.0009607888,0.2856547,0.0003862556,0.0005305968,0.0001603269,0.2208666,0.02266351,0.002114785,0.03056885,0.4260981,0.004198544],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9871373,0.0004253752,0.001447037,0.004060544,0.0007430697,0.003033536,0.00000241001,0.0005104126,0.002640354],"genre_scores_gemma":[0.9746477,0.0001456967,0.0006681003,0.0005342502,0.001521235,0.0005884591,0.0001684147,0.00007394066,0.02165223],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3999918,"threshold_uncertainty_score":0.9997225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01334745029767024,"score_gpt":0.2432285586723854,"score_spread":0.2298811083747152,"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."}}