{"id":"W2037514740","doi":"10.1002/aic.14390","title":"Constrained particle filtering methods for state estimation of nonlinear process","year":2014,"lang":"en","type":"article","venue":"AIChE Journal","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Constraint (computer-aided design); Particle filter; Mathematical optimization; Nonlinear system; Resampling; Sampling (signal processing); State (computer science); Computer science; Mathematics; Algorithm; Filter (signal processing); 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001375649,0.0000716549,0.0001374819,0.00003700738,0.0001196004,0.0001047542,0.0003446546,0.00002984243,0.00001054771],"category_scores_gemma":[0.0003590161,0.00005965176,0.00004953609,0.0001343577,0.00003319607,0.0003301497,0.00004319717,0.0001262336,0.000002309554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007565771,"about_ca_system_score_gemma":0.00003883664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001180948,"about_ca_topic_score_gemma":3.42896e-7,"domain_scores_codex":[0.9991355,0.0001103541,0.0003152648,0.0001254896,0.0001240911,0.0001893219],"domain_scores_gemma":[0.9989937,0.0003625117,0.0002058464,0.0001917829,0.0001607761,0.00008539997],"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":[0.00002626142,0.00005393525,0.0001521099,0.00004373276,0.00002108344,0.000001364074,0.0008529164,0.07690335,0.009095622,0.002137238,0.0003435859,0.9103688],"study_design_scores_gemma":[0.0003880829,0.0001091657,0.0001474801,0.00003714408,0.000006607689,0.00005861379,0.00001575827,0.9518009,0.03767921,0.008273208,0.00141064,0.00007322751],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0445756,0.00003321479,0.9546436,0.0002847461,0.000293852,0.00006131882,0.00000317081,0.00003912628,0.00006537342],"genre_scores_gemma":[0.3706256,0.000005348479,0.6292211,0.00006865142,0.00005649756,0.000002087265,0.00000143652,0.000004341597,0.00001485611],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9102955,"threshold_uncertainty_score":0.2432528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02537370708875693,"score_gpt":0.3530378799003498,"score_spread":0.3276641728115929,"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."}}