{"id":"W2913124573","doi":"10.5267/j.msl.2019.1.006","title":"Application of EWMA chart for monitoring process mean in paper industry","year":2019,"lang":"en","type":"article","venue":"Management Science Letters","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"EWMA chart; Control chart; Chart; Computer science; Process (computing); Operations management; Business; Statistics; Mathematics; Engineering","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":[0.002152546,0.0001155855,0.0001911267,0.000468788,0.0001044349,0.0001089221,0.001244645,0.00004264754,0.00001555465],"category_scores_gemma":[0.0002218825,0.00009939094,0.00003087795,0.001938921,0.0002290134,0.001107116,0.000173579,0.0001596063,0.0000515849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001003387,"about_ca_system_score_gemma":0.00001063757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006346365,"about_ca_topic_score_gemma":9.886322e-7,"domain_scores_codex":[0.996851,0.00001836066,0.000485265,0.0007104394,0.001538703,0.0003961943],"domain_scores_gemma":[0.9988683,0.0002458465,0.0002201928,0.0005017474,0.00009260953,0.00007128491],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004066749,0.00005864007,0.7808633,0.000141439,0.00000561253,0.000002162639,0.0006946787,0.02023123,0.04758549,0.007744611,0.00009386033,0.1425382],"study_design_scores_gemma":[0.002105219,0.0001684322,0.7989029,0.0003191508,0.00002600964,0.000001811112,0.01439859,0.03954343,0.07015085,0.0683082,0.005089846,0.000985585],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7983581,0.000008006299,0.1977575,0.001319126,0.0004551357,0.00079934,0.000002790971,0.00002479991,0.001275201],"genre_scores_gemma":[0.9919321,9.91605e-7,0.007372507,0.000295079,0.00005396581,0.0001290491,3.844984e-7,0.000008591252,0.0002073548],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.193574,"threshold_uncertainty_score":0.4053045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0524331901048649,"score_gpt":0.4021334028881746,"score_spread":0.3497002127833096,"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."}}