{"id":"W3168029116","doi":"10.2478/jaiscr-2021-0013","title":"A New Approach to Detection of Changes in Multidimensional Patterns - Part II","year":2021,"lang":"en","type":"article","venue":"Journal of Artificial Intelligence and Soft Computing Research","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Nonparametric statistics; Kernel density estimation; Fault detection and isolation; Multivariate statistics; Kernel (algebra); Computer science; Edge detection; Jump; Nonparametric regression; Pattern recognition (psychology); Enhanced Data Rates for GSM Evolution; Artificial intelligence; Algorithm; Data mining; Mathematics; Image processing; Machine learning; Image (mathematics); Statistics","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":[],"consensus_categories":[],"category_scores_codex":[0.001302873,0.00007089014,0.0002122792,0.0003396222,0.00008611902,0.00003552333,0.00008567914,0.00006065681,0.00001665432],"category_scores_gemma":[0.0002521544,0.00006685901,0.00004397509,0.0004762159,0.00001934287,0.00004913519,0.0000594055,0.000375347,0.000004654845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004786169,"about_ca_system_score_gemma":0.0000578464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001171603,"about_ca_topic_score_gemma":0.0003634273,"domain_scores_codex":[0.9987316,0.0001132418,0.0004454524,0.0001182782,0.0003778778,0.0002135345],"domain_scores_gemma":[0.9992436,0.0002055428,0.0000519083,0.000083518,0.0002911569,0.0001242536],"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":[0.000102214,0.0001204871,0.000493844,0.000110672,0.0000414288,0.00003010869,0.004283709,0.1019694,0.1724872,0.0002372771,0.0001357745,0.7199878],"study_design_scores_gemma":[0.0001322316,0.0003819577,0.0009363946,0.0004265551,0.000006246752,0.0001412987,0.005936313,0.6512043,0.3381858,0.0004214541,0.002075172,0.0001522972],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8373855,0.0003018321,0.1616163,0.000133197,0.0003769341,0.00008034718,8.117491e-7,0.00001037464,0.00009472617],"genre_scores_gemma":[0.998618,0.00005299825,0.0009113744,0.00001241951,0.0003441746,0.0000011264,2.739309e-7,0.000008579209,0.00005102834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7198355,"threshold_uncertainty_score":0.2726431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09388523869285634,"score_gpt":0.3421888409458216,"score_spread":0.2483036022529652,"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."}}