{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000249266,0.00009141205,0.0001054317,0.0001095831,0.0001434868,0.0002139322,0.0005570208,0.00005651784,0.00003491325],"category_scores_gemma":[0.00004807708,0.00007772259,0.00006979804,0.0004700687,0.00001360552,0.000332291,0.00008153328,0.00006572597,0.00003218294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001329642,"about_ca_system_score_gemma":0.00001480017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003808525,"about_ca_topic_score_gemma":0.000005516714,"domain_scores_codex":[0.9990571,0.00001545776,0.0001923802,0.0002895059,0.0001715967,0.0002739633],"domain_scores_gemma":[0.9991809,0.0002609657,0.00004833029,0.0003777632,0.0000885425,0.00004349802],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003461699,0.00008152848,0.001490085,0.000009163741,0.000005671283,0.00000569641,0.00002739897,0.003055686,0.0003129506,0.7248248,0.221247,0.04893655],"study_design_scores_gemma":[0.0004511983,0.00005088661,0.001827815,0.000007165998,0.000004651339,0.00001257394,0.000008810028,0.3526599,0.00629092,0.05587108,0.5825102,0.0003047897],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0005872955,0.0001742223,0.9853501,0.0004257324,0.0006535993,0.0001083839,0.000006853115,0.0003995792,0.01229423],"genre_scores_gemma":[0.3408147,0.000003955427,0.6571065,0.0003238318,0.000279275,0.000009682663,0.00002084884,0.000008444504,0.001432852],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6689537,"threshold_uncertainty_score":0.3169435,"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."}}