{"id":"W4307400963","doi":"10.1016/j.apm.2022.10.028","title":"A multi-objective approach for designing a tire closed-loop supply chain network considering producer responsibility","year":2022,"lang":"en","type":"article","venue":"Applied Mathematical Modelling","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Supply chain; Weighting; Supply chain network; Constraint (computer-aided design); Reverse logistics; Mathematical optimization; Product (mathematics); Operations research; Linear programming; Fuzzy logic; Computer science; Closed loop; Supply chain management; Business; Engineering; Control engineering; 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":[0.001958639,0.001637962,0.001726163,0.001282465,0.00105535,0.002489429,0.001776513,0.002916012,0.004403463],"category_scores_gemma":[0.002491163,0.001177294,0.001375279,0.001111802,0.0008993478,0.001610902,0.001833445,0.001274339,0.0004684917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001534573,"about_ca_system_score_gemma":0.00182143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008686799,"about_ca_topic_score_gemma":0.007480538,"domain_scores_codex":[0.9991152,0.0003271005,0.00003678919,0.0001828621,0.0002365251,0.0001014918],"domain_scores_gemma":[0.9990146,0.0005920706,0.0001209884,0.00002856421,0.0001922231,0.00005148453],"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":[0.000008915377,0.00001328626,0.00005980563,0.00003020841,0.00001351219,0.00003500843,0.00002010206,0.9951788,0.0003886748,0.00150708,0.00006223097,0.002682374],"study_design_scores_gemma":[0.000003068678,0.00001803488,0.00002239878,0.000004148011,0.000005362194,0.000004029622,0.000008057212,0.9990314,0.00009694613,0.0006554741,0.0001483608,0.000002793445],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0106539,0.0001459942,0.9837209,0.0001331696,0.00002847499,0.00008094567,0.00004764172,0.00009723573,0.00509176],"genre_scores_gemma":[0.750836,0.0003626384,0.2389929,0.0001230317,0.00004690641,0.0006527467,0.0001574096,0.0000992049,0.008729249],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008686799,"threshold_uncertainty_score":0.01727247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04180386699764695,"score_gpt":0.241235150099209,"score_spread":0.1994312831015621,"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."}}