{"id":"W2542134467","doi":"10.1109/acssc.2006.354905","title":"Metrics for Target Tracking","year":2006,"lang":"en","type":"article","venue":"","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"BitTorrent tracker; Tracking (education); Computer science; Artificial intelligence; Kinematics; Computer vision; Covariance; Confidence interval; Pattern recognition (psychology); Algorithm; Mathematics; Statistics; Eye tracking","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":[0.003263762,0.002024606,0.001517264,0.006081372,0.001013349,0.003053034,0.001595178,0.002022873,0.005182062],"category_scores_gemma":[0.02380769,0.0002873722,0.0007640666,0.005152919,0.001294988,0.005384126,0.002308777,0.001965312,0.002688803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002031392,"about_ca_system_score_gemma":0.001008059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002095977,"about_ca_topic_score_gemma":0.00112115,"domain_scores_codex":[0.9962037,0.001156069,0.0003730606,0.0006030973,0.001475869,0.0001882182],"domain_scores_gemma":[0.9931059,0.002813743,0.0009214157,0.00103384,0.001846946,0.0002780632],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00008119477,0.00004811135,0.00186114,0.0005106603,0.00007851353,0.0001091814,0.0001807895,0.06015977,0.002392781,0.6424261,0.02843755,0.2637141],"study_design_scores_gemma":[0.00001779372,0.0001860099,0.002101455,0.0002119086,0.00004342,0.0004205168,0.0001314064,0.1988198,0.001388454,0.7031531,0.09345489,0.00007129527],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006877515,0.0163647,0.9535472,0.001457083,0.0007247448,0.0001780002,0.001849445,0.0008398676,0.01816144],"genre_scores_gemma":[0.3454672,0.0180505,0.6029219,0.001108232,0.002353224,0.00176477,0.008060333,0.0008913467,0.01938246],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006081372,"threshold_uncertainty_score":0.01733571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02023110664659261,"score_gpt":0.2455755436963205,"score_spread":0.2253444370497279,"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."}}