{"id":"W1976774657","doi":"10.1117/12.541894","title":"&lt;title&gt;A randomized heuristic approach for multidimensional association in target tracking&lt;/title&gt;","year":2004,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Heuristic; Computational complexity theory; Computer science; Relaxation (psychology); Mathematical optimization; Tracking (education); Tree (set theory); Algorithm; Artificial intelligence; Mathematics","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":[0.0020637,0.0006187842,0.001054845,0.000750693,0.0007394344,0.001163555,0.001609189,0.001308313,0.005812713],"category_scores_gemma":[0.004155366,0.0004049246,0.0007533908,0.001234806,0.00100659,0.001081972,0.0008791315,0.001379104,0.001436462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001190284,"about_ca_system_score_gemma":0.001775557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003140753,"about_ca_topic_score_gemma":0.006064525,"domain_scores_codex":[0.9984139,0.0009186339,0.00005272723,0.0001999992,0.0002706244,0.0001440373],"domain_scores_gemma":[0.9974184,0.00161997,0.0002437673,0.0003573173,0.0002504846,0.0001100434],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000285773,0.0002583037,0.0007512756,0.0001717336,0.00008849383,0.0001460896,0.00005981195,0.7820049,0.005165528,0.04478931,0.009989876,0.1562889],"study_design_scores_gemma":[0.00003208731,0.00006909403,0.00008440675,0.00001190544,0.000009872747,0.00003176872,0.000009525236,0.9906708,0.00109856,0.005896069,0.002072865,0.00001304454],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008579499,0.0003922798,0.9861478,0.0003584666,0.00009917811,0.0001218959,0.00005821995,0.0004113775,0.003831366],"genre_scores_gemma":[0.1859593,0.0003201902,0.8076454,0.0003862007,0.0001176232,0.0003320644,0.0002247135,0.0002080482,0.004806487],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005812713,"threshold_uncertainty_score":0.01944542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01009906195535383,"score_gpt":0.2192068384838709,"score_spread":0.2091077765285171,"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."}}