{"id":"W2145115346","doi":"10.1039/c4nr02512a","title":"Reduced graphene oxide growth on 316L stainless steel for medical applications","year":2014,"lang":"en","type":"article","venue":"Nanoscale","topic":"Graphene and Nanomaterials Applications","field":"Engineering","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Nicolet Chartrand Knoll (Canada); Université du Québec à Montréal; Université Laval; Institut National de la Recherche Scientifique","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; E.W.R. Steacie Memorial Fund; Western Canada Research Grid; Compute Canada","keywords":"Graphene; X-ray photoelectron spectroscopy; Materials science; Raman spectroscopy; Contact angle; Oxide; Scanning electron microscope; Wetting; Chemical engineering; Alloy; Etching (microfabrication); Nanotechnology; Analytical Chemistry (journal); Composite material; Metallurgy; Chemistry; Layer (electronics); Organic chemistry; Optics","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":[0.0002147997,0.0001589274,0.0002004279,0.0001035482,0.0001302587,0.00002823723,0.0002715395,0.000161468,0.00004648151],"category_scores_gemma":[0.00003901831,0.0001527106,0.00009098304,0.0002485972,0.00004705133,0.00004547007,0.00001972046,0.00008311075,0.00006834617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002577526,"about_ca_system_score_gemma":0.00002054763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001172536,"about_ca_topic_score_gemma":0.00001782411,"domain_scores_codex":[0.9989616,0.00002093883,0.0002755928,0.0002436411,0.0002126741,0.0002855089],"domain_scores_gemma":[0.9992032,0.0001556727,0.00003399723,0.0003690552,0.00006716728,0.0001709228],"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":[0.0000311304,0.0002225194,0.0003020682,0.0002261451,0.00006606562,4.882831e-7,0.0000624042,0.0001537458,0.7156888,0.258265,0.0164733,0.008508308],"study_design_scores_gemma":[0.002113636,0.0001924839,0.01005892,0.00008506632,0.00008685286,0.000007298328,0.00005558365,0.006675663,0.7011399,0.03238913,0.2463357,0.0008597554],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8495001,0.000109935,0.140677,0.0006678942,0.0003242259,0.001277244,0.000107254,0.0008065084,0.00652977],"genre_scores_gemma":[0.9955272,0.00006239526,0.00191946,0.0002031264,0.0002164985,0.001867918,0.00006398932,0.00004948544,0.00008993779],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2298624,"threshold_uncertainty_score":0.6227357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007228814994836089,"score_gpt":0.2253160768667926,"score_spread":0.2180872618719565,"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."}}