{"id":"W132576580","doi":"10.1007/978-1-4020-8883-4_37","title":"Particle Filter Application to Localization","year":2009,"lang":"en","type":"book-chapter","venue":"NATO science for peace and security series. C, Environmental security","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lockheed Martin (Canada); McGill University","funders":"","keywords":"Beacon; Particle filter; Resampling; Computer science; Simple (philosophy); Range (aeronautics); Global Positioning System; Algorithm; Set (abstract data type); Filter (signal processing); Real-time computing; Computer vision; Engineering; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006346797,0.000421441,0.0003599734,0.0001402548,0.0008242951,0.0003932859,0.001123101,0.0003019765,0.00006703773],"category_scores_gemma":[0.00002955663,0.0004376341,0.0001086166,0.0001924683,0.0005537687,0.00124751,0.0006240388,0.0003476877,0.00009217313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002102899,"about_ca_system_score_gemma":0.00005709344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001655217,"about_ca_topic_score_gemma":0.00004503634,"domain_scores_codex":[0.9967149,0.00002143583,0.000437443,0.001391958,0.0008457935,0.0005884377],"domain_scores_gemma":[0.9982815,0.00005288947,0.0002091973,0.0009470413,0.00005116259,0.0004582209],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001962168,0.0004482911,0.0003957215,0.0001528605,0.00004029676,0.00002468,0.01082308,0.0005490801,0.002286126,0.7968435,0.01683332,0.1714069],"study_design_scores_gemma":[0.000376516,0.0004256361,0.0001681097,0.00005959747,0.00002583251,0.00003998326,0.00007440863,0.03767873,0.00216538,0.07926752,0.878876,0.0008423142],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04441628,0.01400478,0.7790598,0.01442458,0.004388682,0.01558935,0.003574318,0.002576112,0.1219662],"genre_scores_gemma":[0.9769807,0.001951667,0.005133239,0.002811411,0.0003798514,0.0001054243,0.0003815059,0.0000643364,0.01219187],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9325644,"threshold_uncertainty_score":0.9998075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007803989961206842,"score_gpt":0.2186311534066202,"score_spread":0.2108271634454134,"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."}}