{"id":"W2761086690","doi":"10.1049/iet-rsn.2017.0162","title":"Data association for target tracking rooted in maximum‐likelihood values","year":2017,"lang":"en","type":"article","venue":"IET Radar Sonar & Navigation","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":"Consejo Nacional de Ciencia y Tecnología","keywords":"Association (psychology); Data association; Maximum likelihood; Tracking (education); Statistics; Computer science; Mathematics; Psychology; Epistemology; Philosophy","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":[0.001730764,0.0001850537,0.0002432832,0.00007805749,0.0006883667,0.0008129953,0.002268235,0.0002081066,0.000007279392],"category_scores_gemma":[0.0004378907,0.0001970961,0.00006441611,0.0001686143,0.00002948043,0.002489243,0.0004257071,0.0002798064,0.00002825959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001659887,"about_ca_system_score_gemma":0.000084688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000159156,"about_ca_topic_score_gemma":0.00009132218,"domain_scores_codex":[0.9977861,0.0001117343,0.0004278531,0.0007104616,0.0005034574,0.0004603894],"domain_scores_gemma":[0.9971259,0.0002736697,0.0005562024,0.001788492,0.0001739915,0.00008172927],"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":[0.00008479132,0.0004039675,0.06141108,0.0001120731,0.0000892941,0.00005889334,0.001876354,0.0008067169,0.002509139,0.007525475,0.06376859,0.8613536],"study_design_scores_gemma":[0.003442703,0.0001613142,0.1589664,0.0005380512,0.00004812558,0.00002044504,0.0001132262,0.5214886,0.003701296,0.1497431,0.1607543,0.001022466],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09176646,0.0005333022,0.895197,0.006094463,0.003226036,0.001011593,0.0008636566,0.0005209661,0.0007864699],"genre_scores_gemma":[0.7593024,0.00005193424,0.237865,0.0001413819,0.0005895504,0.00002549654,0.001853019,0.00003099624,0.0001402508],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8603312,"threshold_uncertainty_score":0.8037344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04307815202157338,"score_gpt":0.3109625544720016,"score_spread":0.2678844024504282,"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."}}