{"id":"W2103098338","doi":"10.1109/radar.2005.1435967","title":"A smoothing rao-blackwellized particle filter for tracking a highly-maneuverable target","year":2005,"lang":"en","type":"article","venue":"","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Smoothing; Particle filter; Tracking (education); Filter (signal processing); Computer science; Particle (ecology); Control theory (sociology); Artificial intelligence; Computer vision; Psychology; Geology","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":[0.001224692,0.0006830345,0.0007304031,0.000622858,0.0003801276,0.0006709555,0.0008462826,0.001102302,0.001006872],"category_scores_gemma":[0.004178996,0.0003649449,0.0006780479,0.0007570158,0.0004839535,0.001028437,0.0005216199,0.001202971,0.0005716526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005482002,"about_ca_system_score_gemma":0.001581931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007714627,"about_ca_topic_score_gemma":0.006922449,"domain_scores_codex":[0.9992445,0.0001629498,0.00004848065,0.000157397,0.0003421004,0.00004467938],"domain_scores_gemma":[0.9984789,0.0006347549,0.0001457936,0.0001932754,0.000494578,0.00005271634],"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":[0.0002434895,0.00007515085,0.001580371,0.0001782107,0.0001734992,0.0001563547,0.0001179208,0.6718401,0.02806293,0.00989968,0.002692303,0.28498],"study_design_scores_gemma":[0.00001180751,0.00004208213,0.0003596029,0.000004199643,0.00001484503,0.00003550653,0.000005934427,0.9932238,0.003616684,0.00120974,0.00146099,0.00001473046],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002770674,0.00006966162,0.9966043,0.00003714316,0.00003894912,0.00001120411,0.00001301907,0.0002481588,0.0002068522],"genre_scores_gemma":[0.2092941,0.0003680296,0.7867643,0.0001478304,0.00009842114,0.000107263,0.0001981083,0.0001007881,0.002921317],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007714627,"threshold_uncertainty_score":0.01533943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02560980662406912,"score_gpt":0.2563438363036329,"score_spread":0.2307340296795638,"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."}}