{"id":"W2765112428","doi":"10.1109/apusncursinrsm.2017.8073367","title":"Millimeter-wave TTD metamaterial Fresnel lens","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Antenna and Metasurface Technologies","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada)","funders":"","keywords":"Metamaterial; Fresnel lens; Extremely high frequency; Optics; Metamaterial antenna; Lens (geology); Millimeter; Bandwidth (computing); Physics; Antenna (radio); Optoelectronics; Dipole antenna; Computer science; Coaxial antenna; Telecommunications","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":[0.00004668555,0.0001241778,0.0001677411,0.00003464298,0.0001311904,0.00007151735,0.0002361364,0.00007403442,0.0001134362],"category_scores_gemma":[0.00005770797,0.00009914507,0.00005258373,0.00001631705,0.0000756759,0.0002730219,0.00007867863,0.00007829145,0.0001337637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001188246,"about_ca_system_score_gemma":0.000002472254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001211424,"about_ca_topic_score_gemma":0.0000169251,"domain_scores_codex":[0.9994792,0.000003066011,0.0001077451,0.0001184214,0.00006600541,0.0002255895],"domain_scores_gemma":[0.9993495,0.000009828004,0.00002526482,0.0005739598,0.00001561647,0.00002578089],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000005253744,0.000009297109,0.0001565033,0.00002451272,0.00007678723,0.00002661699,0.00003587973,0.0003075724,0.9806433,0.002345505,0.001717977,0.0146508],"study_design_scores_gemma":[0.0003846115,0.00003163906,0.002429754,0.00001540598,0.00002879979,0.00000962995,0.00008896652,0.00282496,0.9442831,0.00316849,0.04640935,0.0003252406],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9498855,0.000325325,0.0181276,0.0001689447,0.001275706,0.0001021766,0.00001810228,0.001738103,0.02835855],"genre_scores_gemma":[0.9813223,0.0002655855,0.01712903,0.00001919201,0.00005086992,0.00000753899,0.000001921237,0.00002237009,0.001181193],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04469138,"threshold_uncertainty_score":0.4043019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05091778694323842,"score_gpt":0.2424242661875819,"score_spread":0.1915064792443435,"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."}}