{"id":"W2011512357","doi":"10.1016/j.colsurfa.2015.04.027","title":"High quality Pt–graphene nanocomposites for efficient electrocatalytic nitrite sensing","year":2015,"lang":"en","type":"article","venue":"Colloids and Surfaces A Physicochemical and Engineering Aspects","topic":"Electrochemical sensors and biosensors","field":"Engineering","cited_by":55,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Priority Academic Program Development of Jiangsu Higher Education Institutions; National Natural Science Foundation of China","keywords":"Graphene; Amperometry; X-ray photoelectron spectroscopy; Nanocomposite; Materials science; Cyclic voltammetry; Raman spectroscopy; Chemical engineering; Nitrite; Electrode; Electrochemical gas sensor; Oxide; Electrocatalyst; Electrochemistry; Analytical Chemistry (journal); Nanotechnology; Chemistry; Organic chemistry; Nitrate; Metallurgy","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001169806,0.0002990677,0.0004205539,0.00005182603,0.00006525841,0.00008214742,0.000070494,0.0001123194,4.897875e-7],"category_scores_gemma":[0.00005075161,0.000273517,0.00007764609,0.0002530605,0.0000544983,0.00004908315,0.0000364586,0.0001756643,0.000001155665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005547321,"about_ca_system_score_gemma":0.0000105568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003552707,"about_ca_topic_score_gemma":0.000002168274,"domain_scores_codex":[0.9987988,0.000008099314,0.000244022,0.0003166575,0.0001554756,0.000476934],"domain_scores_gemma":[0.9993184,0.0001634595,0.00002689599,0.000131666,0.00006763777,0.0002919323],"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":[0.00003811075,0.00002582813,0.00002286403,0.0001779613,0.0000560052,0.000001648034,0.00007621887,0.01007614,0.9879032,0.0009084719,0.0001609504,0.0005526206],"study_design_scores_gemma":[0.0008028524,0.00009254024,0.0002162887,0.00006004009,0.00003869344,0.00001319843,0.0000338236,0.1637829,0.8331673,0.000993874,0.0003456149,0.0004528516],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959013,0.002193127,0.001106066,0.00006602787,0.00009877128,0.000207706,0.00001662938,0.0003070756,0.000103274],"genre_scores_gemma":[0.9965763,0.00007637221,0.003082579,0.0000217822,0.0001448033,0.000007969677,0.00002575749,0.00004095927,0.00002346567],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1547358,"threshold_uncertainty_score":0.9999717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00941160476076844,"score_gpt":0.2067771068278719,"score_spread":0.1973655020671034,"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."}}