{"id":"W2950562737","doi":"10.1109/tap.2019.2922945","title":"Augmented Huygens’ Metasurfaces Employing Baffles for Precise Control of Wave Transformations","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Antennas and Propagation","topic":"Metamaterials and Metasurfaces Applications","field":"Materials Science","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Topology (electrical circuits); Computer science; Transformation (genetics); Baffle; Degrees of freedom (physics and chemistry); Physics; Optics; Electrical engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001981878,0.0003342505,0.0003484539,0.0002369631,0.0001365738,0.0005673803,0.00050094,0.0003972131,0.0009168871],"category_scores_gemma":[0.0003869446,0.000186035,0.0002481662,0.0003250377,0.0003894783,0.000558838,0.0004684227,0.0004526424,0.0003412809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002508202,"about_ca_system_score_gemma":0.0001442447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001503126,"about_ca_topic_score_gemma":0.0001730291,"domain_scores_codex":[0.9998401,0.00003993404,0.000008918115,0.0000195656,0.00007212608,0.00001924974],"domain_scores_gemma":[0.9998387,0.00005403749,0.00003099637,0.0000460302,0.00002193636,0.000008239658],"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":[0.0001269272,0.00004549507,0.0004046939,0.0001578348,0.00003481298,0.000215596,0.0001534691,0.08606692,0.6738224,0.1653373,0.001192248,0.0724424],"study_design_scores_gemma":[0.00005677958,0.0002476294,0.0004701407,0.00001898793,0.00001849664,0.0004309032,0.00005067912,0.6225405,0.3250629,0.02042638,0.03062526,0.00005130302],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0996657,0.000382786,0.8896245,0.0001514717,0.00007020307,0.00003478653,0.00008763925,0.0004903931,0.009492585],"genre_scores_gemma":[0.6931649,0.0003647064,0.3025511,0.00006633846,0.00002718218,0.00009486699,0.0001082622,0.00007252294,0.003550137],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009168871,"threshold_uncertainty_score":0.003067315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02620722752775576,"score_gpt":0.2516074280111205,"score_spread":0.2254002004833648,"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."}}