{"id":"W3009301521","doi":"10.1109/tap.2020.2969732","title":"Metamaterials and Metasurfaces—Historical Context, Recent Advances, and Future Directions","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Antennas and Propagation","topic":"Metamaterials and Metasurfaces Applications","field":"Materials Science","cited_by":122,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Metamaterial; Permittivity; Natural materials; Context (archaeology); Optics; Perspective (graphical); Wavelength; Physics; Computer science; Optoelectronics; Materials science; Dielectric; Artificial intelligence","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":[0.0003656523,0.0002134178,0.0003722202,0.00005559102,0.0004722527,0.000163618,0.00006554524,0.00008742054,0.0003291788],"category_scores_gemma":[0.00001457246,0.0001727319,0.00003624517,0.0001886626,0.00009785162,0.0003646413,0.000003510585,0.0001074364,0.00002407399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003567573,"about_ca_system_score_gemma":0.00002273963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004552732,"about_ca_topic_score_gemma":0.00003555384,"domain_scores_codex":[0.9986035,0.0001670141,0.0003768732,0.000483048,0.0001791283,0.0001904242],"domain_scores_gemma":[0.9993163,0.00005426246,0.0001475414,0.000151306,0.0001019609,0.0002286812],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000138975,0.00005627454,0.000005613971,0.00009821219,0.00002183217,0.000001037846,0.000478388,0.00002048289,0.9020451,0.0002976546,0.00008261242,0.0967538],"study_design_scores_gemma":[0.0006614215,0.0002821025,0.0001538184,0.00002225584,0.0002060268,0.00002945506,0.0002631127,0.0008386823,0.3954201,0.0001997073,0.6016133,0.0003100043],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8694584,0.02527953,0.08542258,0.01600152,0.001982401,0.001148671,0.0002850675,0.0002714903,0.0001503252],"genre_scores_gemma":[0.9079251,0.0841139,0.006623551,0.0008035076,0.0001579562,0.0001699683,0.00001064681,0.00003367329,0.0001617262],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6015307,"threshold_uncertainty_score":0.7043803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02832396350244683,"score_gpt":0.248982686793657,"score_spread":0.2206587232912102,"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."}}