{"id":"W4220699573","doi":"10.1002/9781119078166.ch6","title":"Particle Filter","year":2022,"lang":"en","type":"other","venue":"","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":"","keywords":"Particle filter; Resampling; Auxiliary particle filter; Ensemble Kalman filter; Kalman filter; Algorithm; Importance sampling; Gaussian; Extended Kalman filter; Monte Carlo method; Mathematics; Posterior probability; Monte Carlo localization; Computer science; Applied mathematics; Mathematical optimization; Statistics; Bayesian probability; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008734072,0.001636804,0.002031895,0.001281253,0.001039229,0.002520347,0.001893451,0.002097811,0.0147781],"category_scores_gemma":[0.003539991,0.0006244578,0.001093254,0.001962584,0.0005469217,0.00212578,0.001572647,0.001715573,0.009720788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009415146,"about_ca_system_score_gemma":0.001614134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008267277,"about_ca_topic_score_gemma":0.004993238,"domain_scores_codex":[0.9990115,0.0001884048,0.00005088397,0.0002568906,0.0004202699,0.00007209305],"domain_scores_gemma":[0.9992977,0.000249318,0.00005497811,0.00008241513,0.0002891144,0.00002632365],"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":[0.0001438985,0.00008891975,0.001223343,0.0006733766,0.0001772544,0.0001779859,0.0001020799,0.2664145,0.003287027,0.05575889,0.06520057,0.6067522],"study_design_scores_gemma":[0.00003641133,0.00007464289,0.0007175979,0.0001859711,0.00007046481,0.000223136,0.00006131578,0.7836592,0.002456489,0.0372833,0.1751536,0.00007789188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001039029,0.004811526,0.9726303,0.0005229479,0.0008290003,0.0001120478,0.0005470351,0.00152398,0.01798425],"genre_scores_gemma":[0.1450593,0.03115866,0.7174059,0.001389115,0.001792948,0.0009975502,0.006154447,0.001041121,0.09500101],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0147781,"threshold_uncertainty_score":0.0494377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01571316079254252,"score_gpt":0.2275798607705975,"score_spread":0.211866699978055,"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."}}