{"id":"W2072947809","doi":"10.1139/l09-072","title":"Formulation of a pull production system for optimal inventory control of temporary rebar assembly plants","year":2009,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Assembly Line Balancing Optimization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agencia Estatal de Investigación","keywords":"Procurement; Rebar; Inventory control; Production (economics); Precast concrete; Control (management); Computer science; Raw material; Operations management; Operations research; Reliability engineering; Manufacturing engineering; Engineering; Business; Civil engineering; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003626252,0.0001351079,0.0003415875,0.0004962924,0.00002480465,0.0000115348,0.0001169549,0.00009171348,0.000001990155],"category_scores_gemma":[0.000144493,0.0001506685,0.00009507449,0.0001578835,0.000006482855,0.0003278675,0.000001523015,0.0001201618,2.151682e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00024801,"about_ca_system_score_gemma":0.0002422745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005563823,"about_ca_topic_score_gemma":0.0007805285,"domain_scores_codex":[0.9989278,0.00001056889,0.0006220251,0.00007741191,0.0001451273,0.0002170806],"domain_scores_gemma":[0.9991868,0.00002981113,0.0002520365,0.0001224492,0.0002235279,0.0001854442],"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":[0.00001950246,0.000004851745,0.0006168669,0.0003255187,0.00005181795,0.000005469366,0.000148568,0.976572,0.0215455,0.0001465339,0.0003543884,0.0002089883],"study_design_scores_gemma":[0.0009190271,0.0002192939,0.003706177,0.0009179284,0.00005427987,0.0001068491,0.0000970999,0.9724925,0.02083955,0.00001354158,0.0004300066,0.0002037347],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4417101,0.001147148,0.5552765,0.00005242752,0.00107158,0.0003840001,0.00003466528,0.00006009851,0.0002635585],"genre_scores_gemma":[0.9973438,0.000007655041,0.002341006,0.00000308526,0.0002542489,0.000003050647,0.000009639817,0.00003160999,0.000005863185],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5556338,"threshold_uncertainty_score":0.6144084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007065920851720069,"score_gpt":0.1832324377589183,"score_spread":0.1761665169071982,"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."}}