{"id":"W1983353144","doi":"10.1002/aic.12358","title":"Bayesian method for multirate data synthesis and model calibration","year":2010,"lang":"en","type":"article","venue":"AIChE Journal","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Syncrude (Canada); University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Syncrude","keywords":"Flexibility (engineering); Particle filter; Bayesian probability; Computer science; Process (computing); Monte Carlo method; Calibration; Sampling (signal processing); Filter (signal processing); Soft sensor; Data mining; Noise (video); Algorithm; Artificial intelligence; Mathematics; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003847627,0.00120774,0.00158797,0.001769138,0.0006680666,0.001317124,0.001729794,0.001803169,0.004781274],"category_scores_gemma":[0.01048368,0.001260973,0.001443127,0.001579594,0.0009048049,0.001721323,0.001990914,0.00236526,0.001601319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001295667,"about_ca_system_score_gemma":0.002470097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005759995,"about_ca_topic_score_gemma":0.004824792,"domain_scores_codex":[0.998224,0.0006776182,0.0001025915,0.0002755832,0.000636581,0.00008358754],"domain_scores_gemma":[0.9972007,0.001602708,0.0002715158,0.0002882662,0.000577259,0.00005952081],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000134545,0.00005209342,0.0002907896,0.0001990938,0.00009134321,0.00006871689,0.000108095,0.8017335,0.004039755,0.03225815,0.001092067,0.1599319],"study_design_scores_gemma":[0.000010058,0.00001196256,0.00004920762,0.00001362806,0.000006687702,0.0000121732,0.000004433385,0.9931705,0.000810051,0.004900896,0.0009989738,0.00001146621],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003256153,0.00003514978,0.999301,0.00002015379,0.000006920208,0.00001092347,0.00001486262,0.0001301635,0.0001552191],"genre_scores_gemma":[0.08870734,0.000222521,0.9085449,0.00008012956,0.00004266841,0.0003461016,0.0002542338,0.0001804966,0.001621663],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005759995,"threshold_uncertainty_score":0.02034843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02275302660133552,"score_gpt":0.2809463429528549,"score_spread":0.2581933163515194,"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."}}