{"id":"W2619653818","doi":"10.1002/qre.2157","title":"Phase I monitoring with nonparametric mixed‐effect models","year":2017,"lang":"en","type":"article","venue":"Quality and Reliability Engineering International","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Qazvin Islamic Azad University","keywords":"Nonparametric statistics; Smoothing; Computer science; Stability (learning theory); Kernel density estimation; Data mining; Kernel (algebra); Basis (linear algebra); Process (computing); Algorithm; Mathematics; Statistics; Machine learning","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002687486,0.0001859798,0.0003129818,0.0001567738,0.000320963,0.0005950034,0.0008195617,0.00007860915,0.00001674051],"category_scores_gemma":[0.01554466,0.000133377,0.00006078023,0.0001356149,0.0001457787,0.001051384,0.000220753,0.0002925337,0.00001298188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008866057,"about_ca_system_score_gemma":0.00002158449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005263933,"about_ca_topic_score_gemma":0.000001249276,"domain_scores_codex":[0.9973891,0.0000680193,0.0005322002,0.0005717719,0.001205225,0.0002336968],"domain_scores_gemma":[0.9958796,0.002609303,0.0002485332,0.0007269982,0.0003677935,0.0001678082],"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":[0.0009036463,0.0007790435,0.1866771,0.0002547333,0.0001659028,0.00005589173,0.0005978755,0.4585084,0.001613154,0.04564155,0.0000972709,0.3047054],"study_design_scores_gemma":[0.004276958,0.0006260169,0.2424997,0.0001993684,0.00003338017,0.00002420928,0.0001381348,0.6734858,0.006077557,0.06950215,0.002327032,0.0008096828],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5704515,0.0000391825,0.4272528,0.0003205177,0.001123805,0.00009793894,0.00002537811,0.00005386597,0.0006350024],"genre_scores_gemma":[0.9759828,0.00001347821,0.02353066,0.000005716939,0.0002566889,0.00002285989,0.000002219475,0.00001295517,0.0001725688],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4055313,"threshold_uncertainty_score":0.9927478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1200296351193606,"score_gpt":0.4588307505219472,"score_spread":0.3388011154025866,"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."}}