{"id":"W3200602662","doi":"10.1002/pip.3468","title":"Microstructured antireflective encapsulant on concentrator solar cells","year":2021,"lang":"en","type":"article","venue":"Progress in Photovoltaics Research and Applications","topic":"solar cell performance optimization","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; Institut interdisciplinaire d'innovation technologique; University of Ottawa","funders":"Fonds de recherche du Québec – Nature et technologies; Mitacs; Ministère de l'Économie, de la Science et de l'Innovation - Québec; Thomas and Stacey Siebel Foundation","keywords":"Anti-reflective coating; Materials science; Polydimethylsiloxane; Coating; Optoelectronics; Photovoltaic system; Monolayer; Optics; Solar cell; Energy conversion efficiency; Reflection (computer programming); Composite material; Nanotechnology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001767292,0.0001117495,0.0001170861,0.0001465451,0.0001630668,0.0001133247,0.0001204436,0.00009116413,0.00002382933],"category_scores_gemma":[0.00001257585,0.0001170859,0.00001670979,0.0008351933,0.0001740326,0.00008477054,0.0000510968,0.0004171307,0.00002294569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009670744,"about_ca_system_score_gemma":0.00006464023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003461953,"about_ca_topic_score_gemma":0.00001576039,"domain_scores_codex":[0.9989122,0.00003672105,0.0001608754,0.0002712019,0.0002367265,0.0003822488],"domain_scores_gemma":[0.9993608,0.00006862066,0.00001542436,0.0002571825,0.0001923513,0.0001056016],"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":[0.00009527848,0.0005306149,0.02540153,0.0004695297,0.00008464024,0.00007722076,0.001235919,0.003872384,0.9094126,0.001885874,0.001995232,0.05493914],"study_design_scores_gemma":[0.0003994106,0.00004655308,0.001720169,0.0000399916,0.000002747149,0.000007972542,0.0001795234,0.07370653,0.9081651,0.000921652,0.01464183,0.0001685179],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9767197,0.008447457,0.004411089,0.0001020843,0.0001992328,0.002630018,0.0001683903,0.0003231681,0.006998853],"genre_scores_gemma":[0.9917238,0.003232246,0.00411428,0.0000223169,0.00006895284,0.0006945667,0.00007391766,0.00003094664,0.00003900488],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06983415,"threshold_uncertainty_score":0.4774624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.023977660020753,"score_gpt":0.3142176641244661,"score_spread":0.2902400041037131,"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."}}