{"id":"W4225896317","doi":"10.1109/jiot.2022.3167916","title":"Multiple-Target Localization by Millimeter-Wave Radars With Trapezoid Virtual Antenna Arrays","year":2022,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Extremely high frequency; Antenna (radio); Directional antenna; Radar configurations and types; Radar; Remote sensing; Radar engineering details; Radar imaging; Telecommunications; Acoustics; Physics; Geology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004142575,0.0002037277,0.0003060051,0.0001661958,0.0001546768,0.000106973,0.0002707283,0.00005130057,0.0001484176],"category_scores_gemma":[0.00001561164,0.0001774469,0.0001062481,0.0001701312,0.00004607236,0.0004408855,0.00002384392,0.0005967377,0.000002210075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000143175,"about_ca_system_score_gemma":0.00003190575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004884462,"about_ca_topic_score_gemma":0.00000190275,"domain_scores_codex":[0.9984303,0.00007294444,0.0005281498,0.0001595338,0.0005389432,0.0002701892],"domain_scores_gemma":[0.9994059,0.00004761903,0.0002481043,0.000106699,0.00008143946,0.000110204],"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":[0.0005510645,0.0002221591,0.001908447,0.0002799439,0.0008696901,0.0003732311,0.01801858,0.3691666,0.5459343,0.00002435467,0.05263985,0.01001183],"study_design_scores_gemma":[0.001205893,0.0007036976,0.00001764398,0.0002782004,0.00003412491,0.001836751,0.001342515,0.9085267,0.07432988,0.00008175701,0.01125903,0.0003838635],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2799969,0.000951434,0.7176397,0.00002876619,0.0009549467,0.00007781024,0.00001350592,0.00006686215,0.0002701177],"genre_scores_gemma":[0.9972697,0.00002399186,0.002110083,0.0001162901,0.0001185806,0.000004398397,0.000008373141,0.00006025779,0.0002883315],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7172728,"threshold_uncertainty_score":0.7236076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009370229206647493,"score_gpt":0.1858320999857228,"score_spread":0.1764618707790753,"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."}}