{"id":"W2763509819","doi":"10.1007/s13243-017-0036-4","title":"Designing distribution systems with reverse flows","year":2017,"lang":"en","type":"article","venue":"Journal of remanufacturing","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Türkiye Bilimsel ve Teknolojik Araştırma Kurumu","keywords":"Remanufacturing; Reverse logistics; Supply chain; Computer science; Production (economics); Closed loop; Facility location problem; Supply chain network; Heuristic; Mathematical optimization; Downstream (manufacturing); Operations research; Industrial engineering; Supply chain management; Manufacturing engineering; Operations management; Business; Engineering; Control engineering; Mathematics","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":[0.000902604,0.0006822232,0.0005981925,0.0004326591,0.000510654,0.001335162,0.0008794232,0.0008361982,0.003656544],"category_scores_gemma":[0.00176692,0.0006495911,0.000694151,0.000469755,0.0008747365,0.001547185,0.001345983,0.0007120374,0.0004420722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001405382,"about_ca_system_score_gemma":0.001229965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004380161,"about_ca_topic_score_gemma":0.003784988,"domain_scores_codex":[0.9993427,0.0002980099,0.00002084687,0.0001314275,0.00009404388,0.0001129774],"domain_scores_gemma":[0.99927,0.000333872,0.0001288064,0.00008608562,0.0001281931,0.0000530519],"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":[0.00003934423,0.0000301543,0.0002887596,0.00003942686,0.00001508524,0.00007397425,0.00004459404,0.9790041,0.002411709,0.01057125,0.0001838239,0.007297809],"study_design_scores_gemma":[0.00002431657,0.00006106415,0.00008656101,0.000009570686,0.00001319335,0.00002508339,0.0000284838,0.9884864,0.0009645668,0.008810655,0.001483663,0.000006504012],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08049763,0.0001281501,0.9122474,0.0001921575,0.00001921612,0.0001358405,0.00008303174,0.0002703943,0.006426194],"genre_scores_gemma":[0.8823351,0.0002272823,0.1115901,0.000049378,0.00001753647,0.0001685634,0.0001069902,0.00004886733,0.005456229],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004380161,"threshold_uncertainty_score":0.0122323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01337841845878297,"score_gpt":0.2126038821662411,"score_spread":0.1992254637074582,"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."}}