{"id":"W2998450020","doi":"10.1117/12.734360","title":"<title>Computationally efficient assignment-based algorithms for data association for tracking with angle-only sensors</title>","year":2007,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Data association; Association (psychology); Dimension (graph theory); Algorithm; Tracking (education); Assignment problem; Computer science; Tree (set theory); Association scheme; State (computer science); Track (disk drive); Auction algorithm; Association rule learning; Data mining; Mathematics; Mathematical optimization; Artificial intelligence; Statistics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007588421,0.001320987,0.0009665494,0.0008148141,0.0007320278,0.001430155,0.001821365,0.0009827716,0.01543073],"category_scores_gemma":[0.002825223,0.0004999633,0.0007959142,0.0019068,0.000589891,0.002044397,0.001742341,0.002383248,0.01088034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009526745,"about_ca_system_score_gemma":0.001164827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004130956,"about_ca_topic_score_gemma":0.003680864,"domain_scores_codex":[0.9991413,0.0001684019,0.00005436797,0.000221558,0.000333822,0.00008046391],"domain_scores_gemma":[0.9987383,0.0005159438,0.000118797,0.0002524099,0.0003288961,0.00004561541],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002076782,0.0001086051,0.0003669688,0.0001967899,0.00003966164,0.00006316449,0.00008864546,0.1541898,0.007660272,0.05011243,0.02192203,0.7650439],"study_design_scores_gemma":[0.00003186164,0.00004803395,0.0002039191,0.0000349937,0.000009550318,0.00005921809,0.00002199758,0.9455134,0.004397401,0.02608851,0.02356063,0.00003045012],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.000659855,0.0002417551,0.9964536,0.00007604709,0.00008715258,0.00003593467,0.00004546066,0.0007896654,0.001610379],"genre_scores_gemma":[0.03773898,0.0006608029,0.9494842,0.0002144022,0.0001808773,0.0002690737,0.000710157,0.0005107112,0.01023084],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9845693,"threshold_uncertainty_score":0.0516209,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01852621358619418,"score_gpt":0.2461051248791333,"score_spread":0.2275789112929391,"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."}}