{"id":"W1834156195","doi":"10.1109/ijcnn.1992.227334","title":"A comparison between Kalman filters and recurrent neural networks","year":2003,"lang":"en","type":"article","venue":"","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Kalman filter; Extended Kalman filter; Artificial neural network; Computer science; Estimator; Fast Kalman filter; Invariant extended Kalman filter; Alpha beta filter; Artificial intelligence; SIGNAL (programming language); Control theory (sociology); Mathematics; Moving horizon estimation; 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":[0.00009022369,0.00009285072,0.0001241805,0.00002334923,0.0001246166,0.0001186592,0.000259485,0.00003011972,0.00001096452],"category_scores_gemma":[0.000003941918,0.00007650945,0.00002795686,0.0002202031,0.00002906013,0.0001413032,0.00008561427,0.0001232658,0.000006205972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006891441,"about_ca_system_score_gemma":0.000004548248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000573541,"about_ca_topic_score_gemma":0.000005150466,"domain_scores_codex":[0.9992407,0.00004291877,0.0001575843,0.0002618933,0.00008374581,0.0002131369],"domain_scores_gemma":[0.9994722,0.00008221147,0.00004299546,0.0002712396,0.00001527867,0.0001160567],"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":[0.000002004773,0.0001078783,0.1244583,0.000008845372,0.00002596747,0.000003807101,0.0002135698,0.008664097,0.00003935468,0.317453,0.04276438,0.5062588],"study_design_scores_gemma":[0.0001833998,0.00007099659,0.02150995,0.000005913694,0.000006893332,0.00000752127,0.00001204597,0.9473873,0.0001005018,0.001181462,0.02932817,0.0002058275],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09615681,0.0003308616,0.8979375,0.001599169,0.0002226571,0.0002068258,7.174727e-7,0.0001740501,0.003371385],"genre_scores_gemma":[0.9907054,0.00001576177,0.008762413,0.000313358,0.00006051891,0.00001214766,0.000001718023,0.000004090587,0.0001245907],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9387232,"threshold_uncertainty_score":0.3119965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03804759846307454,"score_gpt":0.2969830682251434,"score_spread":0.2589354697620689,"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."}}