{"id":"W7114802852","doi":"10.1109/access.2025.3643368","title":"Smooth Variable Structure Filter in Random Finite Set Applications","year":2025,"lang":"","type":"article","venue":"IEEE Access","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Canada Research Chairs","keywords":"Robustness (evolution); Control theory (sociology); Filter (signal processing); Filter design; Filtering problem; Ensemble Kalman filter; Computational complexity theory; Adaptive filter; Invariant extended Kalman filter","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":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0004926967,0.0004314719,0.0005683076,0.0004908535,0.0004454122,0.001775104,0.003978247,0.0004124992,0.0006740766],"category_scores_gemma":[0.00009476778,0.0004258128,0.0001129849,0.003491377,0.0001419719,0.001327154,0.0008922714,0.0008827625,0.00006780805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008351586,"about_ca_system_score_gemma":0.0004163653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003824021,"about_ca_topic_score_gemma":0.000124704,"domain_scores_codex":[0.9964088,0.0002814406,0.0008930685,0.001234244,0.0003980517,0.0007844115],"domain_scores_gemma":[0.9963129,0.001070019,0.0002539286,0.00200319,0.0002054215,0.0001545754],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004332851,0.000606123,0.01858353,0.0006465729,0.0001899739,0.00008571459,0.001327259,0.4792982,0.0007235415,0.04298278,0.2045335,0.2505896],"study_design_scores_gemma":[0.005073836,0.00003531285,0.004820577,0.0007008681,0.00008723754,0.000008649758,0.0000333034,0.4074538,0.001344032,0.04358423,0.5358923,0.0009658711],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003140371,0.001068522,0.9818789,0.0008760638,0.004804681,0.0009700776,0.0004698419,0.0001555628,0.006635966],"genre_scores_gemma":[0.9821305,0.000392625,0.0111009,0.003370039,0.0006352125,0.0001872096,0.0001378927,0.00003070062,0.00201487],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9789902,"threshold_uncertainty_score":0.9998194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02218027026312816,"score_gpt":0.2996228002315166,"score_spread":0.2774425299683884,"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."}}