{"id":"W2109593202","doi":"","title":"Track purity and current assignment ratio for target tracking and identification evaluation","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":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Clutter; Track (disk drive); Identification (biology); Computer science; Tracking (education); Radar tracker; Sensor fusion; Tracking system; Real-time computing; Artificial intelligence; Data mining; Radar; Kalman filter; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01655301,0.001838704,0.001710054,0.006864067,0.0009316697,0.002647009,0.001430986,0.001746413,0.002629277],"category_scores_gemma":[0.07053286,0.0003451107,0.0009441291,0.004860817,0.001289801,0.004353281,0.002081275,0.001145317,0.00101806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001761076,"about_ca_system_score_gemma":0.001318392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001729958,"about_ca_topic_score_gemma":0.001293698,"domain_scores_codex":[0.9751913,0.007276462,0.002637199,0.001391359,0.01243368,0.001069993],"domain_scores_gemma":[0.9420998,0.03258928,0.00657849,0.004789492,0.01279233,0.001150583],"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":[0.002909543,0.001216323,0.07228959,0.001513309,0.0008722187,0.0004421935,0.0006070708,0.3457021,0.03975702,0.04059333,0.01121538,0.482882],"study_design_scores_gemma":[0.00009982555,0.002922402,0.03334081,0.0002007172,0.000331397,0.001309431,0.0005506215,0.87795,0.05895182,0.01188965,0.0122176,0.0002358252],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1550454,0.00438921,0.8140087,0.0004999087,0.0002548158,0.00104664,0.002171517,0.003035686,0.01954815],"genre_scores_gemma":[0.7674032,0.001010185,0.2250003,0.0001873007,0.0001538755,0.0008103625,0.002674041,0.0003560544,0.002404675],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01655301,"threshold_uncertainty_score":0.0875417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1042448596321978,"score_gpt":0.3197986134460219,"score_spread":0.2155537538138241,"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."}}