{"id":"W2175711167","doi":"10.1016/j.apm.2015.11.027","title":"A review of mathematical inventory models for reverse logistics and the future of its modeling: An environmental perspective","year":2015,"lang":"en","type":"review","venue":"Applied Mathematical Modelling","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":160,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reverse logistics; Economic order quantity; Greenhouse gas; Production (economics); Supply chain; Operations research; Order (exchange); Computer science; Product (mathematics); Environmental economics; Inventory control; Business; Economics; Engineering; Marketing; 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":[0.002976293,0.0006610174,0.002927618,0.0002494862,0.0001111385,0.00006900916,0.0007077112,0.0002867448,0.00004562519],"category_scores_gemma":[0.0001553004,0.0004413977,0.0005147724,0.0002828082,0.0003488839,0.0003316034,0.0005528836,0.0003698741,0.00002142114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001824793,"about_ca_system_score_gemma":0.00009091345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005916328,"about_ca_topic_score_gemma":2.730151e-7,"domain_scores_codex":[0.9966038,0.00005898077,0.001597919,0.0006460852,0.0006527005,0.0004404791],"domain_scores_gemma":[0.997395,0.0003436291,0.00109862,0.0008216193,0.0002862335,0.00005491206],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003485628,0.0001610125,2.734255e-9,0.2864704,0.0001369657,0.000001030792,0.000177088,0.01099014,2.827076e-8,0.6932771,0.0001858294,0.008565653],"study_design_scores_gemma":[0.0003878158,0.0000078413,6.618674e-11,0.0127914,0.001913961,0.000001995262,0.001716338,0.5062773,3.724313e-8,0.4444131,0.03225328,0.0002369811],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[5.962529e-7,0.6251296,0.367776,0.00007509499,0.00003163248,0.00403386,0.0000185368,0.00002994497,0.002904736],"genre_scores_gemma":[0.0001934347,0.986042,0.01172467,0.000323905,0.0005313015,0.0008930286,0.00008882606,0.0001436156,0.00005921046],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.4952871,"threshold_uncertainty_score":0.9998038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08846830086581768,"score_gpt":0.296746611175347,"score_spread":0.2082783103095293,"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."}}