{"id":"W973550985","doi":"10.1002/adom.201800995","title":"Broadband Metamaterial Absorbers","year":2018,"lang":"en","type":"article","venue":"Advanced Optical Materials","topic":"Metamaterials and Metasurfaces Applications","field":"Materials Science","cited_by":637,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"National Key Research and Development Program of China; China Postdoctoral Science Foundation; National Natural Science Foundation of China; Office of Science; Volkswagen Foundation; U.S. Department of Energy","keywords":"Metamaterial; Materials science; Thermophotovoltaic; Photodetection; Plasmon; Broadband; Optoelectronics; Photovoltaics; Terahertz radiation; Nanophotonics; Optics; Photovoltaic system; Physics; Photodetector; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0009004064,0.0003473003,0.0006463334,0.00006684996,0.00034928,0.0003678086,0.0005097585,0.000147728,0.0178102],"category_scores_gemma":[0.0002229218,0.0002835243,0.00007591309,0.0001811839,0.0005193411,0.0004458333,0.0001945119,0.00005346197,0.007560895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004078141,"about_ca_system_score_gemma":0.00004591249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003341603,"about_ca_topic_score_gemma":0.00000706784,"domain_scores_codex":[0.9972472,0.0001498189,0.0007945256,0.0007047544,0.0003765542,0.0007271224],"domain_scores_gemma":[0.998423,0.00009816976,0.0002324616,0.0007700305,0.0002108142,0.0002655335],"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":[0.0002140997,0.00005798943,0.000002913001,0.00002523876,0.00001342294,0.000003265823,0.00005681333,0.000005990088,0.9822634,0.01624413,0.0003774042,0.0007353502],"study_design_scores_gemma":[0.0006492411,0.0001772546,0.0003047784,0.00002213681,0.0000578126,0.00001635775,0.00002624923,0.00000231827,0.9622121,0.003180046,0.03300049,0.0003511926],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9888087,0.00006369544,0.001317735,0.0002447992,0.004010523,0.0005234276,0.0001875037,0.0003176409,0.004526005],"genre_scores_gemma":[0.9436148,0.00003665347,0.05421558,0.0003495895,0.0009785988,0.0001784505,0.00004059382,0.00005970001,0.0005260106],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05289784,"threshold_uncertainty_score":0.9999617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0159210125711234,"score_gpt":0.2815168205134605,"score_spread":0.2655958079423371,"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."}}