{"id":"W4281479779","doi":"10.36227/techrxiv.19805971","title":"Skew Filtering for Online State Estimation and Control","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Kalman filter; Curse of dimensionality; Noise (video); Skew; Computer science; Dimension (graph theory); Algorithm; Metric (unit); Filter (signal processing); Mathematical optimization; Gaussian; Estimation of distribution algorithm; Distribution (mathematics); Mathematics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008668383,0.0007928983,0.0007967876,0.0004028657,0.0003957422,0.0007199582,0.0004178082,0.0006953693,0.002073868],"category_scores_gemma":[0.002529963,0.0002981594,0.0004809911,0.0005318502,0.0006560261,0.00110244,0.0008457091,0.000894498,0.0004569658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000697671,"about_ca_system_score_gemma":0.001007058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003234075,"about_ca_topic_score_gemma":0.002631462,"domain_scores_codex":[0.9993729,0.0001529651,0.00003873771,0.000142356,0.0002375207,0.00005557336],"domain_scores_gemma":[0.9994156,0.0002630923,0.00007859913,0.00009683526,0.0001294042,0.00001645433],"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":[0.0001754581,0.00005990203,0.0006838269,0.000135341,0.00004228669,0.00005362087,0.00007828286,0.6503621,0.01098907,0.04009879,0.002229918,0.2950915],"study_design_scores_gemma":[0.000002579453,0.0000227843,0.0001123992,0.000004572605,0.000002542321,0.000009348312,0.000003794187,0.9925928,0.001285271,0.005117805,0.000842071,0.000004115779],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00364209,0.0001669656,0.9950177,0.00005529915,0.00003199212,0.00001091059,0.00001763105,0.0002188893,0.0008385354],"genre_scores_gemma":[0.7163342,0.000785961,0.2768053,0.0001648051,0.0001382711,0.0001455871,0.0002167687,0.0001471882,0.005261971],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003234075,"threshold_uncertainty_score":0.006937742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009339779376535295,"score_gpt":0.2417311072385617,"score_spread":0.2323913278620264,"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."}}