{"id":"W2037030364","doi":"10.1016/j.mcm.2012.10.029","title":"A continuous review<mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" altimg=\"si35.gif\" display=\"inline\" overflow=\"scroll\"><mml:mrow><mml:mo>(</mml:mo><mml:mi>s</mml:mi><mml:mo>,</mml:mo><mml:mi>Q</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:math>inventory system with priority customers and arbitrarily distributed lead times","year":2012,"lang":"lv","type":"article","venue":"Mathematical and Computer Modelling","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wilfrid Laurier University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Type (biology); Computer science; Poisson distribution; Algorithm; Economic shortage; Mathematics; Operations research; Statistics; Philosophy","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","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00248451,0.00116402,0.0007629293,0.0004207537,0.001584811,0.002142481,0.001413759,0.001263469,0.003337325],"category_scores_gemma":[0.0003089926,0.001640165,0.001249069,0.0008769523,0.001119084,0.002010464,0.002036259,0.001391883,0.001296073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003449067,"about_ca_system_score_gemma":0.0003204928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000725157,"about_ca_topic_score_gemma":0.00008469194,"domain_scores_codex":[0.9913461,0.0002719237,0.002103342,0.001800257,0.002156189,0.002322188],"domain_scores_gemma":[0.9951137,0.0007496967,0.001796631,0.00136171,0.0002479696,0.0007302762],"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":[0.0006769127,0.0006183275,0.00003441301,0.01131561,0.001567881,0.000462177,0.001204874,0.003172437,0.0001084128,0.9485269,0.03003092,0.002281102],"study_design_scores_gemma":[0.002120294,0.000700529,0.00002578242,0.007132439,0.002713953,0.0005999837,0.00163812,0.9625474,0.0111569,0.002240368,0.00725328,0.001870946],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8934445,0.006573499,0.05214985,0.0007948172,0.002241288,0.00029244,0.0001950071,0.0005447671,0.04376385],"genre_scores_gemma":[0.9876898,0.001442443,0.003968185,0.002164641,0.002780589,0.000648991,0.0006058703,0.0004926416,0.000206841],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.959375,"threshold_uncertainty_score":0.999715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01925236071729048,"score_gpt":0.2176891046543442,"score_spread":0.1984367439370537,"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."}}