{"id":"W2009720286","doi":"10.1002/aic.11080","title":"Autoassociative neural networks for robust dynamic data reconciliation","year":2007,"lang":"en","type":"article","venue":"AIChE Journal","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Kalman filter; Computer science; Fractionating column; Noise (video); Artificial neural network; Dynamic data; Filter (signal processing); Process (computing); Online model; Computation; Control theory (sociology); Artificial intelligence; Control engineering; Distillation; Algorithm; Control (management); Engineering; Mathematics; Computer vision","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":[0.00113975,0.00009222851,0.0001319607,0.00005729324,0.0001336067,0.0000715097,0.0001886048,0.00009737068,0.00001804101],"category_scores_gemma":[0.0001044333,0.00008709295,0.00005582923,0.0001027454,0.000006438021,0.0002616326,0.00001379678,0.0003023236,0.000005979702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002223295,"about_ca_system_score_gemma":0.00001174043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005602881,"about_ca_topic_score_gemma":0.000244532,"domain_scores_codex":[0.9992007,0.00002618428,0.000295984,0.0000964226,0.0001189569,0.0002617607],"domain_scores_gemma":[0.9994686,0.0001270394,0.00009532495,0.0001580791,0.00006924346,0.00008175795],"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":[0.00006990211,0.00001615994,0.0005873843,0.00001934816,0.0002515146,0.000009758212,0.0003700104,0.7031912,0.001070535,0.00001708002,0.01927801,0.2751191],"study_design_scores_gemma":[0.000587172,0.00002648794,0.002886371,0.00001002409,0.00002160908,0.00005393447,0.0002107832,0.9873871,0.00001650119,0.00002653587,0.008666525,0.0001069306],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03561347,0.0008428519,0.9582933,0.0002321782,0.003861334,0.0002142955,0.00002277455,0.0001922315,0.0007275258],"genre_scores_gemma":[0.9978054,0.00004237339,0.0009169395,0.00008992911,0.0007924507,0.000003817328,0.0000249673,0.00002380128,0.000300389],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9621919,"threshold_uncertainty_score":0.3551548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02566352150534206,"score_gpt":0.2649440832402891,"score_spread":0.239280561734947,"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."}}