{"id":"W2115365970","doi":"10.1109/icif.2003.177383","title":"Single target tracking in clutter: performance comparison between pda and vda","year":2003,"lang":"en","type":"article","venue":"","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Clutter; Computer science; Tracking (education); Computer vision; Artificial intelligence; Radar tracker; Radar; Psychology; 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":[0.0004200013,0.0001540304,0.0002429163,0.0001145539,0.0001303753,0.0002106738,0.0003889619,0.00008697142,0.00004238671],"category_scores_gemma":[0.00003257652,0.0001403102,0.00002565994,0.0003605469,0.00004316966,0.0006051374,0.0001176512,0.0002499699,0.00002874507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002598108,"about_ca_system_score_gemma":0.0000165578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002411384,"about_ca_topic_score_gemma":0.00002545951,"domain_scores_codex":[0.9985527,0.00009552632,0.0003497867,0.0004156474,0.0002053501,0.0003809657],"domain_scores_gemma":[0.9992326,0.0001695915,0.00007139074,0.0003940533,0.00002965215,0.0001027519],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003918172,0.000115338,0.8200174,0.000021834,0.000007403611,0.000009460987,0.0007487199,0.0009061476,0.0002152256,0.00718824,0.002746352,0.16802],"study_design_scores_gemma":[0.002810471,0.0005472841,0.4039905,0.0002801022,0.00001766205,0.00008917294,0.0004305079,0.3403295,0.03984434,0.004584727,0.205291,0.001784694],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7959744,0.0002908179,0.1951634,0.0001911851,0.0003240692,0.0001032587,0.000002083075,0.0001810049,0.007769786],"genre_scores_gemma":[0.9103478,0.00001829533,0.08926018,0.0002026163,0.00005116727,0.000002691982,0.000005458076,0.000008739869,0.0001030189],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4160268,"threshold_uncertainty_score":0.5721684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03306238814781085,"score_gpt":0.260892245255923,"score_spread":0.2278298571081122,"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."}}