{"id":"W2737703135","doi":"","title":"Loop Based Facility Planning and Material Handling","year":2002,"lang":"en","type":"article","venue":"RePEc: Research Papers in Economics","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Group for Research in Decision Analysis; HEC Montréal","funders":"","keywords":"Material handling; Sizing; Material flow; Facility management; Material requirements planning; Engineering; Manufacturing engineering; Materials management; Computer science; Operations management; Production (economics); Business","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000223468,0.00008721233,0.000115964,0.000110614,0.00007724467,0.00005316592,0.00006853954,0.00007051589,0.00007962882],"category_scores_gemma":[0.00009608595,0.00009841793,0.00001373529,0.00003505286,0.00006689645,0.00007450549,0.00002855699,0.0002040406,0.000004023285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001173932,"about_ca_system_score_gemma":0.000005882874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003596962,"about_ca_topic_score_gemma":0.000004716747,"domain_scores_codex":[0.9993032,0.00002375135,0.0001550144,0.0001819915,0.00005444812,0.0002816402],"domain_scores_gemma":[0.9996272,0.0001288828,0.00001265443,0.0001556995,0.00001233551,0.00006322216],"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":[0.00001073572,0.000008409229,0.0007296199,0.00003896393,0.000004491453,0.000006028699,0.00006570498,0.9492974,0.0001902989,0.00001205838,0.00001000094,0.04962626],"study_design_scores_gemma":[0.0003621707,0.00002413531,0.0008633399,0.00002562762,0.000001339863,0.000002244771,0.00007528841,0.992382,0.003220618,0.0001103405,0.002781026,0.0001518959],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9637937,0.0001533288,0.005268916,0.0000415619,0.000303222,0.0002448621,0.00005490772,0.0002166179,0.02992291],"genre_scores_gemma":[0.9968547,0.0004703428,0.002425499,0.000008635158,0.00004106142,0.00001428212,0.00001506473,0.00001458049,0.0001558599],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04947437,"threshold_uncertainty_score":0.4013367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03181325443690155,"score_gpt":0.2635214543322168,"score_spread":0.2317081998953152,"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."}}