{"id":"W2048929145","doi":"10.1109/mfi.2010.5604458","title":"Random finite set theoretic based soft/hard data fusion with application for target tracking","year":2010,"lang":"en","type":"article","venue":"","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Fusion; Tracking (education); Set (abstract data type); Sensor fusion; Data set; Artificial intelligence; Algorithm","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":[0.001635073,0.0005173738,0.001066978,0.00083789,0.0006004471,0.001329154,0.0009077352,0.0007483414,0.001595212],"category_scores_gemma":[0.003416873,0.0002246159,0.000909458,0.0007147476,0.001102139,0.001461978,0.001303205,0.0008380441,0.0003971719],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007083839,"about_ca_system_score_gemma":0.0004787212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008261529,"about_ca_topic_score_gemma":0.0006650292,"domain_scores_codex":[0.9987778,0.0003420427,0.00008221834,0.0002054954,0.0005336108,0.00005873011],"domain_scores_gemma":[0.9987177,0.0007506829,0.0001310471,0.0001844167,0.0001700993,0.00004601438],"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":[0.0005126866,0.0001702895,0.001329615,0.000421796,0.0001892364,0.0005551192,0.0004613279,0.4805993,0.0467957,0.1154158,0.001923094,0.3516261],"study_design_scores_gemma":[0.00001384862,0.0001246289,0.0003318965,0.00002037668,0.00003180825,0.0001954866,0.0000401071,0.9550803,0.01411705,0.0272098,0.002792779,0.00004188323],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01408131,0.0004171019,0.9832292,0.0001841028,0.00005523131,0.00005108539,0.00002873479,0.0003266973,0.001626522],"genre_scores_gemma":[0.6397648,0.0005559204,0.3574769,0.0001858946,0.0000733214,0.0001093151,0.0001020089,0.00005743855,0.001674498],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001635073,"threshold_uncertainty_score":0.008647203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02943109416624475,"score_gpt":0.2607910673691176,"score_spread":0.2313599732028729,"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."}}