{"id":"W3032472579","doi":"10.1109/access.2020.2997560","title":"An Applied Method for Clustering Extended Targets With UHF Radar","year":2020,"lang":"en","type":"article","venue":"IEEE Access","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"National Key Research and Development Program of China; China Scholarship Council; National Natural Science Foundation of China","keywords":"Ultra high frequency; Computer science; Cluster analysis; Radar; Remote sensing; Telecommunications; Artificial intelligence; Geology","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":[0.0007297463,0.0007312155,0.0005907062,0.001515744,0.0005978371,0.0007274709,0.001340848,0.001041022,0.001607182],"category_scores_gemma":[0.001716209,0.0003115622,0.0008447345,0.00159175,0.0005320508,0.0009487189,0.000825501,0.0007078376,0.001082838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004823485,"about_ca_system_score_gemma":0.0006226977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002549433,"about_ca_topic_score_gemma":0.002282164,"domain_scores_codex":[0.9989541,0.0001479281,0.00005144666,0.0003022924,0.0004737416,0.00007052576],"domain_scores_gemma":[0.9992818,0.0001206692,0.00005954727,0.0001323355,0.0003831855,0.00002239824],"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":[0.0001658325,0.00008354647,0.000938492,0.000212494,0.0001072975,0.0001286433,0.0002774779,0.1105105,0.08088223,0.01115098,0.001960718,0.7935818],"study_design_scores_gemma":[0.00001582428,0.00007924096,0.001067238,0.00001477258,0.00002959875,0.0003054238,0.00005466601,0.9550623,0.03163973,0.004001054,0.007682289,0.00004792882],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003216135,0.00008089878,0.9957955,0.00002258228,0.00004238811,0.00002866201,0.00001695452,0.0002996792,0.0004971899],"genre_scores_gemma":[0.07804739,0.0001902689,0.9188572,0.00007088394,0.0000547083,0.00009875888,0.0001275514,0.00009694971,0.002456355],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002549433,"threshold_uncertainty_score":0.005376577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04105499892984051,"score_gpt":0.3241775053710572,"score_spread":0.2831225064412167,"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."}}