{"id":"W4413240925","doi":"10.1007/s13571-025-00374-y","title":"Non-Parametric Multivariate Control Chart Using Copula Entropy","year":2025,"lang":"en","type":"article","venue":"Sankhya B","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Innovative Research Group Project of the National Natural Science Foundation of China","keywords":"Copula (linguistics); Multivariate statistics; Parametric statistics; Control chart; Econometrics; Statistics; Mathematics; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0009580712,0.0001933322,0.0004376794,0.0005186802,0.0002708713,0.0002174976,0.0006326641,0.00009077658,0.0002129146],"category_scores_gemma":[0.009167964,0.0001551228,0.00009554593,0.002084759,0.0001140951,0.0003109871,0.0001430237,0.0002449506,0.0002929149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001303217,"about_ca_system_score_gemma":0.0001122104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000654299,"about_ca_topic_score_gemma":0.000002477721,"domain_scores_codex":[0.9972243,0.0001068562,0.000681808,0.0006126165,0.0009209221,0.0004535532],"domain_scores_gemma":[0.9963303,0.002399106,0.0002101892,0.0005399436,0.0003807874,0.000139659],"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":[0.001066808,0.0007364613,0.3496348,0.0001490347,0.000385437,0.0002935496,0.0008368246,0.04846998,0.09895357,0.08823246,0.01235852,0.3988826],"study_design_scores_gemma":[0.00453779,0.000101145,0.0948176,0.0001586758,0.0001121069,0.00000739058,0.0005128793,0.5710739,0.006047779,0.2979245,0.02400075,0.0007054221],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0685948,0.0002466311,0.9260389,0.0002221359,0.001694735,0.0003017169,0.00003458424,0.00006635299,0.002800184],"genre_scores_gemma":[0.9747841,0.000003533544,0.02345963,0.0002782168,0.0001486268,0.00001431349,0.000001366741,0.00001323754,0.001296938],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9061893,"threshold_uncertainty_score":0.9991782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09456391720644183,"score_gpt":0.462522832748288,"score_spread":0.3679589155418461,"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."}}