{"id":"W4254603053","doi":"10.1109/wsc.1989.718753","title":"Watmins Jit/Kanban Benchmark Summary and Recommendations","year":2005,"lang":"en","type":"article","venue":"1989 Winter Simulation Conference Proceedings","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Kanban; Benchmark (surveying); Computer science; Queue; Process (computing); Work (physics); Production (economics); Queueing theory; Operations research; Inventory control; Manufacturing engineering; Industrial engineering; Control (management); Production control; Work in process; Operations management; Engineering; Mechanical engineering; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009996916,0.001342644,0.0009963205,0.00292896,0.0009753202,0.004890026,0.003247568,0.0007943632,0.01539318],"category_scores_gemma":[0.04596989,0.000394172,0.0009109253,0.004054652,0.0004026038,0.003558042,0.0009809191,0.001152308,0.003372081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002789869,"about_ca_system_score_gemma":0.003626981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0111129,"about_ca_topic_score_gemma":0.01081367,"domain_scores_codex":[0.9906596,0.003291707,0.000736052,0.0004850834,0.004366359,0.0004611597],"domain_scores_gemma":[0.9632357,0.01093134,0.001103756,0.003512451,0.02034037,0.0008763708],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00175105,0.001133312,0.01200164,0.00205195,0.0002233006,0.0002509752,0.0002979569,0.2494347,0.006845227,0.06672242,0.2381366,0.4211509],"study_design_scores_gemma":[0.0004379647,0.001680745,0.0107892,0.001698907,0.0002510409,0.0001960987,0.001461203,0.7631357,0.02985388,0.04533494,0.1449663,0.0001940262],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.166193,0.008606287,0.4499769,0.02125535,0.003577738,0.00224582,0.02512845,0.03061014,0.2924064],"genre_scores_gemma":[0.5249364,0.005561585,0.3853547,0.001624935,0.0003953813,0.002002721,0.04145446,0.003521526,0.03514831],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01539318,"threshold_uncertainty_score":0.05286938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1060390690557638,"score_gpt":0.4041947965707841,"score_spread":0.2981557275150203,"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."}}