{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001454415,0.000382418,0.0002004082,0.0003787202,0.0001345291,0.0001423873,0.0004210508,0.0005008579,0.0008107241],"category_scores_gemma":[0.0002384358,0.000193025,0.0002823957,0.0002104855,0.0001298061,0.0001673745,0.0001737234,0.0002329692,0.0007291318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002747707,"about_ca_system_score_gemma":0.0001547033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004359719,"about_ca_topic_score_gemma":0.001228083,"domain_scores_codex":[0.9997775,0.00001679778,0.0000114816,0.00002797047,0.0001487703,0.00001752292],"domain_scores_gemma":[0.9998825,0.00001592452,0.00003197828,0.00001502822,0.00003869719,0.00001588042],"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":[0.000008678601,0.00000315881,0.00004630201,0.00004209049,0.000001576019,0.00003521692,0.000005211575,0.00004679503,0.9978819,0.00004132093,0.00006777424,0.001819844],"study_design_scores_gemma":[0.000005615055,0.0001768039,0.001752761,0.000009098416,0.000009209977,0.000335321,0.00001039994,0.001554445,0.9898403,0.00006226848,0.006233218,0.00001052783],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9028832,0.01093577,0.06861538,0.0007496758,0.0004792051,0.0002876642,0.001231948,0.001023808,0.01379336],"genre_scores_gemma":[0.8988096,0.003386257,0.09022266,0.000149627,0.00006069863,0.00005752434,0.0007279305,0.00006851215,0.006517045],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008107241,"threshold_uncertainty_score":0.002712131,"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."}}