{"id":"W4229076918","doi":"10.1088/2053-1583/ac6cf3","title":"International interlaboratory comparison of Raman spectroscopic analysis of CVD-grown graphene","year":2022,"lang":"en","type":"article","venue":"2D Materials","topic":"Graphene research and applications","field":"Materials Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"Fundação de Amparo à Pesquisa do Estado de Minas Gerais; Gobierno de Aragón; Ministerio de Ciencia e Innovación; Engineering and Physical Sciences Research Council; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Graphene Flagship","keywords":"Raman spectroscopy; Graphene; Materials science; Analytical Chemistry (journal); Nanotechnology; Chemistry; Environmental chemistry; Optics; Physics","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":[0.06081644,0.001490284,0.0008460322,0.005500086,0.001877214,0.002831081,0.002504108,0.002158411,0.00247677],"category_scores_gemma":[0.06233048,0.0006259364,0.001606838,0.003931198,0.00231807,0.001075338,0.004678653,0.001427789,0.001139958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00165442,"about_ca_system_score_gemma":0.00170956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003161621,"about_ca_topic_score_gemma":0.004469784,"domain_scores_codex":[0.9120871,0.0394414,0.005711495,0.01710502,0.02399474,0.001660308],"domain_scores_gemma":[0.9026597,0.03814428,0.007331873,0.01955214,0.03120807,0.001103942],"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":[0.005084356,0.003286259,0.2527269,0.003339679,0.004791973,0.0005493076,0.01456349,0.01157078,0.433852,0.009829768,0.01039253,0.2500129],"study_design_scores_gemma":[0.000235498,0.004616447,0.3616176,0.0007164936,0.00184135,0.001005254,0.004561274,0.01299021,0.5705801,0.004982576,0.03636971,0.0004834603],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7754807,0.003775237,0.1872064,0.0008396507,0.00123276,0.002565044,0.006926795,0.00166595,0.02030743],"genre_scores_gemma":[0.8820146,0.0005253924,0.1038044,0.0005933065,0.0001989928,0.001830002,0.007597466,0.0004674808,0.002968436],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06081644,"threshold_uncertainty_score":0.321632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02291902617094464,"score_gpt":0.3334090951583758,"score_spread":0.3104900689874311,"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."}}