{"id":"W2642447559","doi":"10.23977/isspj.2016.11003","title":"Load Monitoring Based on the Auxiliary Particle Filter Algorithm","year":2016,"lang":"en","type":"article","venue":"Information Systems and Signal Processing Journal","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Particle filter; Auxiliary particle filter; Algorithm; Set (abstract data type); Filter (signal processing); MATLAB; Particle (ecology); Computer science; Ensemble Kalman filter; Artificial intelligence; Kalman filter; Extended Kalman filter; Computer vision","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007789711,0.0006799651,0.0009780681,0.000694238,0.0004230308,0.0008611013,0.001100739,0.0008841121,0.001465439],"category_scores_gemma":[0.002677747,0.0003257248,0.0006674802,0.0007683786,0.00040928,0.0012456,0.0007212214,0.0008373676,0.0004840128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005483609,"about_ca_system_score_gemma":0.0009113572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005426058,"about_ca_topic_score_gemma":0.002814814,"domain_scores_codex":[0.9994408,0.0001241216,0.00003176481,0.0001408106,0.0002169671,0.00004542043],"domain_scores_gemma":[0.9992843,0.0002782866,0.00007333187,0.00007534881,0.0002625697,0.00002614551],"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":[0.0002715159,0.0001008099,0.002846895,0.000164486,0.0001003269,0.0001140367,0.0001732383,0.6407269,0.00960667,0.0207613,0.00397297,0.3211607],"study_design_scores_gemma":[0.00000806104,0.0000149403,0.0002442272,0.000003302331,0.000007598625,0.00001617726,0.000003857882,0.9964663,0.000872294,0.001591321,0.0007655147,0.000006396188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004567448,0.00008679722,0.9938635,0.00006294341,0.00003058313,0.00002111815,0.00002823728,0.0002889474,0.001050489],"genre_scores_gemma":[0.5462393,0.0007277753,0.4456299,0.0002069402,0.0001454732,0.0002527505,0.0004059992,0.0001470993,0.006244784],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005426058,"threshold_uncertainty_score":0.01078892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02087971252578561,"score_gpt":0.2319021884219691,"score_spread":0.2110224758961834,"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."}}