{"id":"W4390187134","doi":"10.1109/access.2023.3346433","title":"A New Strategy for Combining Nonlinear Kalman Filters With Smooth Variable Structure Filters","year":2023,"lang":"en","type":"article","venue":"IEEE Access","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"FedDev Ontario","keywords":"Kalman filter; Nonlinear system; Computer science; Filter (signal processing); Control theory (sociology); State space; Nonlinear filter; Extended Kalman filter; Algorithm; Mathematics; Filter design; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001691484,0.0002364268,0.0002487133,0.0001585419,0.0002713029,0.0008513773,0.001867302,0.0001125513,0.00006608066],"category_scores_gemma":[0.00002150126,0.000194605,0.00005296332,0.001099712,0.00003489896,0.001013352,0.0002156176,0.0002290993,0.00002031615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002146307,"about_ca_system_score_gemma":0.0001634017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000223277,"about_ca_topic_score_gemma":0.00004417006,"domain_scores_codex":[0.9982032,0.00003642728,0.0002551009,0.0006130892,0.0003196155,0.0005725946],"domain_scores_gemma":[0.9985492,0.0002683334,0.0001333872,0.0007631489,0.00009068178,0.0001952336],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001652113,0.00006186635,0.002014129,0.0001444769,0.0001429275,0.0001171196,0.0008481996,0.4036503,0.001653543,0.01101857,0.5074449,0.07273879],"study_design_scores_gemma":[0.004180939,0.0007199777,0.003133386,0.0003645589,0.0000678289,0.00006027627,0.0001810788,0.8715439,0.005419412,0.01645203,0.09639103,0.00148559],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03904936,0.00003062621,0.9563763,0.0004712836,0.002029951,0.0004001454,0.000159972,0.0008333262,0.0006490221],"genre_scores_gemma":[0.6531985,0.00002759869,0.3417825,0.001518152,0.001129731,0.00005064704,0.0004169834,0.00009942886,0.001776413],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6145938,"threshold_uncertainty_score":0.8209851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03968949069558284,"score_gpt":0.2980129807448304,"score_spread":0.2583234900492475,"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."}}