{"id":"W3090386704","doi":"10.3390/s20195689","title":"Particle Filter for Randomly Delayed Measurements with Unknown Latency Probability","year":2020,"lang":"en","type":"article","venue":"Sensors","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Probability density function; Recursion (computer science); Latency (audio); Control theory (sociology); Particle filter; Filter (signal processing); Noise (video); Algorithm; Mathematics; Convergence (economics); Computer science; Applied mathematics; Statistics; Kalman filter; Artificial intelligence; 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":[],"consensus_categories":[],"category_scores_codex":[0.0002965825,0.0001625936,0.0002061109,0.00001474056,0.0001566692,0.0001132197,0.0004562083,0.00005587417,0.00002445191],"category_scores_gemma":[0.0001369769,0.0001203066,0.0000750476,0.0002865873,0.00004987072,0.0002087653,0.00008511512,0.0001169588,0.00005025029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001698373,"about_ca_system_score_gemma":0.00003722871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001150532,"about_ca_topic_score_gemma":0.00001769424,"domain_scores_codex":[0.9984201,0.000100282,0.0002622227,0.000523627,0.0003204957,0.0003733046],"domain_scores_gemma":[0.9989356,0.0001364109,0.00007992528,0.0004715781,0.0001729245,0.0002035221],"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":[0.01839726,0.00260645,0.08411422,0.001106639,0.00147089,0.0003150587,0.02877528,0.3216594,0.0283061,0.06316954,0.1445082,0.305571],"study_design_scores_gemma":[0.01430612,0.002019407,0.002997397,0.00008801324,0.0001082038,0.00003148833,0.00008802403,0.8634756,0.03136758,0.004321293,0.07993709,0.001259821],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7189326,0.0001017036,0.271588,0.006789845,0.0003579454,0.00101177,0.000026467,0.0005918449,0.0005998385],"genre_scores_gemma":[0.9451911,0.000004199987,0.05350178,0.0009692741,0.0001313097,0.00003704967,0.00001129553,0.00001708775,0.0001369472],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5418162,"threshold_uncertainty_score":0.4905959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06808194585835943,"score_gpt":0.2459707790604429,"score_spread":0.1778888332020835,"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."}}