{"id":"W4386630867","doi":"10.1109/oceanslimerick52467.2023.10244275","title":"Joint Detection and Tracking for Compact HFSWR","year":2023,"lang":"en","type":"article","venue":"","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"National Natural Science Foundation of China","keywords":"Tracking (education); Computer science; Detector; Artificial intelligence; Computer vision; Radar tracker; Low probability of intercept radar; Tracking system; Track-before-detect; Transmission (telecommunications); Object detection; Radar; Radar imaging; Pattern recognition (psychology); Telecommunications; Radar engineering details; Kalman filter","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":[0.0008605345,0.000529996,0.0007235687,0.0004916694,0.0002510259,0.0005988628,0.0007270253,0.0008270454,0.001037332],"category_scores_gemma":[0.0011608,0.0002850969,0.000431706,0.0004808089,0.0003649122,0.001242523,0.0009370869,0.0005777379,0.0008945492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002442494,"about_ca_system_score_gemma":0.0005622148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008634524,"about_ca_topic_score_gemma":0.001080368,"domain_scores_codex":[0.9987754,0.0001751662,0.00005389828,0.0002534652,0.0006275449,0.000114457],"domain_scores_gemma":[0.999299,0.0001624857,0.0001622033,0.0001827944,0.0001609243,0.00003244205],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003786512,0.0001899426,0.001677159,0.0001648208,0.00006661464,0.0001973166,0.0001519482,0.06075558,0.3256663,0.006906093,0.001942757,0.6019028],"study_design_scores_gemma":[0.00005128441,0.0004961891,0.002456721,0.00001435119,0.00003550532,0.0006667266,0.00003057444,0.8873136,0.1006626,0.003117054,0.005101751,0.00005357504],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02244308,0.0001959457,0.9753683,0.00005368473,0.00003952085,0.00002718348,0.00002304395,0.0008248487,0.001024439],"genre_scores_gemma":[0.5032502,0.0002455341,0.4924216,0.0001714244,0.00007849571,0.00007392826,0.0002110222,0.00006571322,0.003482097],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001037332,"threshold_uncertainty_score":0.004550934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03801636821164812,"score_gpt":0.2382358508333284,"score_spread":0.2002194826216803,"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."}}