{"id":"W2741845085","doi":"10.1021/acs.jpcc.7b04437","title":"PtRu Alloy Nanoparticles. 2. Chemical and Electrochemical Surface Characterization for Methanol Oxidation","year":2017,"lang":"en","type":"article","venue":"The Journal of Physical Chemistry C","topic":"Electrocatalysts for Energy Conversion","field":"Energy","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Polytechnique Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; China Scholarship Council","keywords":"X-ray photoelectron spectroscopy; Platinum; Catalysis; Ruthenium; Electrochemistry; Nanoparticle; Platinum nanoparticles; Annealing (glass); Materials science; Inorganic chemistry; Electrocatalyst; Alloy; Analytical Chemistry (journal); Chemistry; Chemical engineering; Electrode; Nanotechnology; Physical chemistry; Metallurgy","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":[0.0002518162,0.0005358336,0.0004003872,0.0006347219,0.000288008,0.0002563755,0.0004958336,0.0007325948,0.002548596],"category_scores_gemma":[0.000360839,0.0003123322,0.0002893862,0.0004603101,0.0001430911,0.0002396588,0.0001296275,0.0003588035,0.0009581685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003685181,"about_ca_system_score_gemma":0.0001260663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007100689,"about_ca_topic_score_gemma":0.001510084,"domain_scores_codex":[0.9996593,0.00002802542,0.00003423206,0.0001030228,0.0001317014,0.00004379858],"domain_scores_gemma":[0.9998521,0.00002754235,0.00002986978,0.000020745,0.00006059356,0.00000917293],"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":[0.00003812132,0.00001292798,0.0001253678,0.00005238348,0.000003700856,0.00003744147,0.00001281462,0.00006991912,0.9973639,0.00005085186,0.00005459132,0.002178089],"study_design_scores_gemma":[0.000002735505,0.0000706545,0.001358711,0.000004378651,0.000009396159,0.0001347841,0.00001263658,0.0009169469,0.9959267,0.00002181096,0.001538137,0.000003210931],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9522353,0.003453373,0.03188301,0.0001696141,0.0001359514,0.0002735999,0.001516624,0.0005505705,0.009781991],"genre_scores_gemma":[0.958858,0.001536248,0.02927398,0.00007859431,0.00003062368,0.0002688283,0.001682813,0.0001097205,0.008161289],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002548596,"threshold_uncertainty_score":0.008525908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008910076256376194,"score_gpt":0.2389301756472544,"score_spread":0.2300200993908783,"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."}}