{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009388982,0.00004159683,0.00006374231,0.00004285989,0.00004981425,0.00004169666,0.00001206011,0.00002142014,0.000004192041],"category_scores_gemma":[0.000007085948,0.00003597595,0.00001679459,0.00007052265,0.000003380178,0.00007232904,0.0000019368,0.00002676542,0.000007752406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001019952,"about_ca_system_score_gemma":0.000001512676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001046372,"about_ca_topic_score_gemma":0.00001392525,"domain_scores_codex":[0.9997476,0.000002200831,0.00007574175,0.00005103905,0.00003331687,0.00009007789],"domain_scores_gemma":[0.9999154,0.00001902936,0.000006234594,0.00002836149,0.000008794116,0.00002217975],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006893094,0.000004161725,0.0003318269,0.0008347589,0.00004568505,0.000003831992,0.0007634967,0.02569919,0.7425436,0.00029278,0.004076612,0.2253972],"study_design_scores_gemma":[0.0001962256,0.00002272022,0.004362368,0.00004093543,0.000004876482,0.000009807774,0.0003083882,0.9115989,0.07755745,0.0004014786,0.005379451,0.0001174205],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7931857,0.0002158117,0.2000924,0.00004753262,0.0003150996,0.0001492208,0.000001685786,0.0008550481,0.005137487],"genre_scores_gemma":[0.9995808,0.000004978301,0.0001228617,0.000004940688,0.00007085317,0.000003146733,6.85877e-7,0.00001241874,0.0001992923],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8858997,"threshold_uncertainty_score":0.1467057,"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."}}