{"id":"W2022292064","doi":"10.1109/camsap.2013.6714084","title":"Particle filter implementation of the multi-Bernoulli filter for superpositional sensors","year":2013,"lang":"en","type":"article","venue":"","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Filter (signal processing); Bernoulli's principle; Particle filter; Tracking (education); Computer science; Algorithm; Control theory (sociology); Artificial intelligence; Computer vision; Engineering","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":[0.001384432,0.0004123633,0.0006461734,0.0003997552,0.0004585006,0.0008486935,0.0009691027,0.001109468,0.003364164],"category_scores_gemma":[0.00451064,0.0003030624,0.0005565534,0.0005610019,0.0004974133,0.001253184,0.0006373127,0.001353621,0.0009258695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006965907,"about_ca_system_score_gemma":0.001513912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006067541,"about_ca_topic_score_gemma":0.005721036,"domain_scores_codex":[0.999374,0.0001494281,0.00003683706,0.00009718703,0.0002977201,0.00004487448],"domain_scores_gemma":[0.9988148,0.0005639956,0.00007421584,0.0001966077,0.0003171521,0.00003319514],"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":[0.0002794938,0.0001208875,0.001568673,0.0001692328,0.00009646734,0.000207648,0.0002507829,0.5296829,0.02281993,0.1306086,0.004531158,0.3096642],"study_design_scores_gemma":[0.00001413636,0.00003696389,0.0001823027,0.000006693777,0.000007662138,0.00005189619,0.000006801134,0.9864938,0.004407722,0.005780689,0.002998753,0.00001264722],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001366608,0.000028919,0.9976035,0.00005701676,0.0000343455,0.00001427483,0.00001422997,0.0001410986,0.0007400204],"genre_scores_gemma":[0.1554846,0.0002281817,0.8390167,0.000169776,0.00005566904,0.0001756268,0.0001264572,0.00006153416,0.004681551],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006067541,"threshold_uncertainty_score":0.01206446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02687945762408078,"score_gpt":0.277308398269734,"score_spread":0.2504289406456532,"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."}}