{"id":"W2153818665","doi":"10.1109/iscas.2008.4541860","title":"MEMS automotive collision avoidence radar beamformer","year":2008,"lang":"en","type":"article","venue":"","topic":"Acoustic Wave Resonator Technologies","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Lens (geology); Microelectromechanical systems; Beam steering; Radar; Microstrip; Optics; Luneburg lens; Materials science; Footprint; Beam (structure); Engineering; Electrical engineering; Optoelectronics; Antenna (radio); Physics; Aerospace engineering","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":[0.00004626211,0.0001243767,0.0001295369,0.00007985435,0.00007717714,0.000007571538,0.0001900588,0.0001136185,0.0001046831],"category_scores_gemma":[0.0001126851,0.0001049598,0.00003550907,0.0002127581,0.00009906108,0.0001350225,0.00004879744,0.0001625455,0.0002310665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009993779,"about_ca_system_score_gemma":0.00001560206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001350855,"about_ca_topic_score_gemma":0.000002103852,"domain_scores_codex":[0.9993153,0.000003348888,0.0001339306,0.00012733,0.0001903362,0.0002297465],"domain_scores_gemma":[0.9996291,0.00006153778,0.00001277858,0.0002121655,0.00004187343,0.00004253339],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003452116,0.0002140872,0.005340549,0.0002985591,0.0003809916,0.0006683785,0.002468389,0.1376495,0.3741499,0.009454588,0.4312202,0.03812038],"study_design_scores_gemma":[0.0007096407,0.0001554827,0.01065577,0.00008389757,0.00002790799,0.0003743017,0.001331981,0.0667047,0.859647,0.001876317,0.05739395,0.001039041],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8237156,0.0006891967,0.134807,0.0001231652,0.0003287314,0.0002148704,0.000008889259,0.00438412,0.03572852],"genre_scores_gemma":[0.983107,0.000358047,0.01536808,0.00003300976,0.00002569801,0.000009122029,0.000001501696,0.00002352781,0.001074034],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4854972,"threshold_uncertainty_score":0.4280134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01298128953313192,"score_gpt":0.198885164360078,"score_spread":0.185903874826946,"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."}}