{"id":"W2118207253","doi":"","title":"Weight partitioned Probability Hypothesis Density filters","year":2011,"lang":"en","type":"article","venue":"International Conference on Information Fusion","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Context (archaeology); Filter (signal processing); Particle filter; Computer science; Algorithm; Deconvolution; Set (abstract data type); State (computer science); Singleton; Probability density function; Mathematics; Statistics; Artificial intelligence; Pattern recognition (psychology); Computer vision","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":[0.002609229,0.001046079,0.00128709,0.001146085,0.0004577636,0.001950534,0.00207808,0.001783287,0.00426019],"category_scores_gemma":[0.01675138,0.0007805207,0.001097648,0.001150217,0.001003276,0.003485355,0.001947001,0.001560873,0.001232215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008882982,"about_ca_system_score_gemma":0.001302961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002121748,"about_ca_topic_score_gemma":0.001466608,"domain_scores_codex":[0.9981964,0.0004156903,0.0001175673,0.0004985577,0.0005980257,0.0001737205],"domain_scores_gemma":[0.995378,0.002430822,0.0003288036,0.000728706,0.00103487,0.00009880953],"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":[0.0008354153,0.0001531597,0.002030078,0.0002758669,0.0002430068,0.0001964063,0.000294816,0.4407459,0.01862336,0.08256332,0.003275456,0.4507633],"study_design_scores_gemma":[0.00003725235,0.00008182901,0.0005743561,0.00002232898,0.0000316308,0.00007145922,0.00003050247,0.9656152,0.005661952,0.02564996,0.002196507,0.0000270089],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003160157,0.00006182696,0.9961117,0.00003650085,0.0000196777,0.00002855922,0.00004682164,0.0001616386,0.0003731512],"genre_scores_gemma":[0.2847586,0.0004933194,0.7075818,0.0002050234,0.0001700482,0.0005099211,0.000892935,0.0002211666,0.005167238],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00426019,"threshold_uncertainty_score":0.01425171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07083073807537754,"score_gpt":0.2406731824986677,"score_spread":0.1698424444232901,"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."}}