{"id":"W4304190232","doi":"10.1038/s41598-022-20851-y","title":"Synthesis of multi-band reflective polarizing metasurfaces using a generative adversarial network","year":2022,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Metamaterials and Metasurfaces Applications","field":"Materials Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Adversarial system; Generative adversarial network; Generative grammar; Computer science; Artificial intelligence; Deep learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002452163,0.0004294956,0.0002421086,0.0001510543,0.000119974,0.0003896572,0.0003187116,0.0005400039,0.001062019],"category_scores_gemma":[0.0004500716,0.0002075524,0.0003502983,0.0001447614,0.0005505909,0.0003475855,0.0005505549,0.0004960766,0.0002760178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002722942,"about_ca_system_score_gemma":0.0001631713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001115643,"about_ca_topic_score_gemma":0.0001860272,"domain_scores_codex":[0.9999118,0.00001977995,0.000002616139,0.00002014951,0.00003230718,0.00001340821],"domain_scores_gemma":[0.9998468,0.00007104113,0.00003527789,0.00002301321,0.00001439493,0.000009445612],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007514627,0.00005338923,0.0004396827,0.000111249,0.00003618454,0.0002525048,0.0001052689,0.6973996,0.2294846,0.04412629,0.0006183283,0.02729763],"study_design_scores_gemma":[0.000009858853,0.00004878934,0.00005545692,0.000006576393,0.000004793667,0.00005273605,0.00001263628,0.9683241,0.02625617,0.004239311,0.0009806434,0.00000885832],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1297282,0.0002047312,0.8571057,0.0003268445,0.00006157235,0.00007305646,0.00005999137,0.0002516037,0.01218833],"genre_scores_gemma":[0.8229831,0.0001776006,0.1728452,0.0001043715,0.00001198915,0.00008547326,0.0000487097,0.00004902043,0.003694474],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001062019,"threshold_uncertainty_score":0.003552735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05299994496078447,"score_gpt":0.3017333660883093,"score_spread":0.2487334211275248,"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."}}