{"id":"W2293302691","doi":"10.1080/00949655.2015.1106542","title":"On-line monitoring data quality of high-dimensional data streams","year":2015,"lang":"en","type":"article","venue":"Journal of Statistical Computation and Simulation","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China; Canadian Foundation for Dietetic Research","keywords":"Univariate; Control chart; Data stream mining; Data mining; Computer science; Statistical process control; Multivariate statistics; Statistics; Data stream; Process (computing); Mathematics; Machine learning; Telecommunications","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.004028191,0.000117729,0.0004246562,0.0001732451,0.00007343987,0.00009778884,0.000560035,0.00005069012,0.00001910569],"category_scores_gemma":[0.03252931,0.00008843852,0.00001651867,0.0002660762,0.0001200846,0.0009048986,0.0003198071,0.0002151871,0.00000717694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004090394,"about_ca_system_score_gemma":0.0001310051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002119158,"about_ca_topic_score_gemma":0.000002050631,"domain_scores_codex":[0.9955747,0.0003230822,0.001500535,0.0003521993,0.002123429,0.0001260818],"domain_scores_gemma":[0.983815,0.01290944,0.0009955951,0.0004644563,0.001553257,0.0002622934],"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":[0.0003637409,0.00008717335,0.00151497,0.00001041374,0.00001492535,0.000008439158,0.00005982905,0.8170666,0.00002031308,0.006130085,0.0002788816,0.1744447],"study_design_scores_gemma":[0.000869346,0.0002445289,0.01484391,0.00003241049,0.00001689108,0.000003811079,0.0001178146,0.7401779,0.00001923902,0.2435741,0.00002821909,0.00007189511],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1586668,0.00005858885,0.8401866,0.0001264729,0.0004584542,0.00005524304,0.0004180917,0.000006231797,0.00002355281],"genre_scores_gemma":[0.832741,0.000002222879,0.1669383,0.00001634176,0.0001850773,1.20211e-7,0.0001015488,0.000006790932,0.000008678237],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6740742,"threshold_uncertainty_score":0.9756201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5798239156926426,"score_gpt":0.5692615365766077,"score_spread":0.01056237911603486,"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."}}