{"id":"W2280949289","doi":"10.1039/c5ee03580e","title":"Scalable fabrication of micron-scale graphene nanomeshes for high-performance supercapacitor applications","year":2016,"lang":"en","type":"article","venue":"Energy & Environmental Science","topic":"Supercapacitor Materials and Fabrication","field":"Materials Science","cited_by":138,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Light Source (Canada); Saskatoon Medical Imaging","funders":"","keywords":"Graphene; Fabrication; Supercapacitor; Scalability; Nanotechnology; Materials science; Scale (ratio); Optoelectronics; Capacitance; Computer science; Electrode; Chemistry; Physics; Medicine","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":[0.0001011043,0.0002439619,0.0001189095,0.0002347957,0.0001388738,0.0002617674,0.0003555095,0.0003834945,0.001168331],"category_scores_gemma":[0.0002660719,0.0001495943,0.0001357148,0.0001399321,0.0001188056,0.0005018435,0.0003301704,0.0003934473,0.0004164401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003451813,"about_ca_system_score_gemma":0.0001981141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004750727,"about_ca_topic_score_gemma":0.002217295,"domain_scores_codex":[0.9999373,0.000003415168,0.000004235759,0.0000131542,0.00003176968,0.00001006854],"domain_scores_gemma":[0.9999367,0.00001485533,0.00000928186,0.00001402653,0.00001679997,0.000008361569],"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":[0.0000127433,0.00001283121,0.000102845,0.00007475966,0.000005099131,0.00007555973,0.0000147089,0.000519537,0.991053,0.0006025948,0.0005146381,0.007011627],"study_design_scores_gemma":[0.000008402404,0.00006539311,0.0009692627,0.000009027334,0.000005137139,0.0001243807,0.00002866009,0.007798527,0.9857404,0.0005477418,0.004692337,0.00001069988],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9216264,0.005141061,0.05234744,0.001344992,0.0006002724,0.0002062693,0.002439972,0.001469123,0.01482438],"genre_scores_gemma":[0.9525868,0.001142403,0.04265421,0.00008531426,0.00002264917,0.00006384553,0.0004503404,0.00003280969,0.002961661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001168331,"threshold_uncertainty_score":0.003908515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006367704162584899,"score_gpt":0.1880553316373413,"score_spread":0.1816876274747564,"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."}}