{"id":"W4386846417","doi":"10.1080/03610926.2023.2256439","title":"A combined adaptive double sampling and variable sampling interval control chart for monitoring three-level products","year":2023,"lang":"en","type":"article","venue":"Communication in Statistics- Theory and Methods","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Control chart; EWMA chart; Chart; Computer science; Sampling (signal processing); \\bar x and R chart; Shewhart individuals control chart; Data mining; Statistics; Mathematics; Process (computing)","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":[0.00249557,0.0007960773,0.0006988425,0.001763522,0.0004434724,0.001242697,0.001058956,0.0004385651,0.000948568],"category_scores_gemma":[0.005934005,0.0002131355,0.0004853813,0.001376883,0.0007025781,0.001168347,0.0005728727,0.0007811532,0.0002147276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006753291,"about_ca_system_score_gemma":0.001083711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003193161,"about_ca_topic_score_gemma":0.001904549,"domain_scores_codex":[0.9969653,0.0005820159,0.0002477675,0.0006010056,0.001497281,0.0001066379],"domain_scores_gemma":[0.9953897,0.001452226,0.0006893658,0.000533046,0.001806762,0.0001288365],"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":[0.0007950051,0.0001813867,0.006621974,0.0003710862,0.00008174203,0.0001555787,0.0002810206,0.1567888,0.06583831,0.01563951,0.002601025,0.7506446],"study_design_scores_gemma":[0.00005683724,0.0005328486,0.004061622,0.00003227075,0.00005832187,0.0001856673,0.00003347984,0.9400775,0.04433651,0.003100089,0.007428211,0.00009658599],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01347665,0.0002241882,0.9843625,0.00003357861,0.0000474728,0.0001105088,0.00008214088,0.0008626338,0.0008003606],"genre_scores_gemma":[0.5280744,0.0003179267,0.4694285,0.00005959456,0.00008228396,0.0003205912,0.0003231235,0.00007421432,0.001319412],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003193161,"threshold_uncertainty_score":0.01319802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4280437233153634,"score_gpt":0.5407164894476421,"score_spread":0.1126727661322787,"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."}}