{"id":"W2076465973","doi":"10.5267/j.ijiec.2014.7.006","title":"A production inventory model with exponential demand rate and reverse logistics","year":2014,"lang":"en","type":"article","venue":"International Journal of Industrial Engineering Computations","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Finished good; Supply chain; Profit (economics); Economic order quantity; Production (economics); Imperfect; Inventory control; Production schedule; Operations research; Computer science; Reverse logistics; Holding cost; Idle; Raw material; Schedule; Operations management; Business; Economics; Microeconomics; Engineering; Marketing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00116541,0.001504526,0.001213411,0.0009949853,0.000505424,0.00255271,0.003262879,0.001941962,0.004866796],"category_scores_gemma":[0.001913169,0.001007173,0.001501097,0.001593468,0.0009043128,0.002782081,0.001096418,0.001311449,0.0011019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001652817,"about_ca_system_score_gemma":0.001568363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01043058,"about_ca_topic_score_gemma":0.003703778,"domain_scores_codex":[0.9989582,0.000245628,0.00006542823,0.0002734728,0.0002513633,0.0002058691],"domain_scores_gemma":[0.9992574,0.0002493541,0.0001746472,0.00006328979,0.0001966693,0.00005866537],"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":[0.00007422857,0.00003903235,0.0004637671,0.00007954417,0.00002160119,0.0003466225,0.0000619873,0.9738264,0.001278953,0.01988663,0.0003919044,0.003529372],"study_design_scores_gemma":[0.00002118276,0.00004219708,0.0001385447,0.00001004403,0.00001881969,0.00005986666,0.00001599529,0.9946185,0.000203432,0.004094303,0.0007642228,0.00001301253],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07955201,0.001228608,0.8850834,0.000752112,0.0001418955,0.0002048114,0.0009702168,0.0005673599,0.03149971],"genre_scores_gemma":[0.9086909,0.001450374,0.046925,0.0001180591,0.0000730446,0.0003770195,0.0007251264,0.0001000901,0.04154041],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01043058,"threshold_uncertainty_score":0.02073973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03566176938265155,"score_gpt":0.2256872786693783,"score_spread":0.1900255092867268,"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."}}