{"id":"W1529669168","doi":"10.1002/qre.454","title":"An economic model for \\font\\twelveit=cmti10 scaled 1600$\\overline{\\kern‐0.85ex\\hbox{\\twelveit X}}$\\nopagenumbers\\end and <i>R</i> charts with time‐varying parameters","year":2002,"lang":"en","type":"article","venue":"Quality and Reliability Engineering International","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Weibull distribution; Control chart; Selection (genetic algorithm); Statistics; \\bar x and R chart; X-bar chart; Variance (accounting); Mathematics; Overline; Chart; Engineering; Process (computing); Control limits; Computer science; Economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003311293,0.0008314664,0.000899965,0.001035524,0.0007044694,0.002845631,0.002437355,0.001884257,0.00659119],"category_scores_gemma":[0.007139992,0.0007979555,0.001057936,0.0007938804,0.001446512,0.002413825,0.001066842,0.001569438,0.000701751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004386843,"about_ca_system_score_gemma":0.002412115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01707732,"about_ca_topic_score_gemma":0.007685549,"domain_scores_codex":[0.9984095,0.0006430272,0.0000480431,0.000286755,0.0003711876,0.000241543],"domain_scores_gemma":[0.9968359,0.001989538,0.0004370848,0.0001412153,0.0004285299,0.0001678643],"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":[0.00005651819,0.00004631756,0.0005969087,0.00002689615,0.00001910139,0.00008224329,0.00003741268,0.9311836,0.0003779983,0.06197195,0.0006303497,0.004970666],"study_design_scores_gemma":[0.00001493267,0.00002008427,0.0002189049,0.000005676776,0.000009908304,0.000009614802,0.00001252472,0.9909861,0.0001181979,0.00777632,0.0008175884,0.00001014128],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09907272,0.0005633677,0.8722487,0.001700803,0.00009707482,0.0003518435,0.0005317332,0.0002422109,0.02519152],"genre_scores_gemma":[0.926311,0.0005866206,0.04534761,0.000100008,0.0000493586,0.0005748644,0.0002684977,0.00007589049,0.02668631],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01707732,"threshold_uncertainty_score":0.03395587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.072865741913077,"score_gpt":0.3614251984810491,"score_spread":0.2885594565679722,"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."}}