{"id":"W2770104093","doi":"10.1016/j.apcatb.2017.11.070","title":"Effect of preparation method on the performance of silver-zirconia catalysts for soot oxidation in diesel engine exhaust","year":2017,"lang":"en","type":"article","venue":"Applied Catalysis B: Environmental","topic":"Catalytic Processes in Materials Science","field":"Materials Science","cited_by":61,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa; National Research Council Canada; Natural Resources Canada","funders":"Natural Resources Canada","keywords":"Catalysis; Diesel exhaust; Soot; Diesel particulate filter; X-ray photoelectron spectroscopy; Cubic zirconia; Incipient wetness impregnation; Materials science; Adsorption; Scanning electron microscope; Inorganic chemistry; Nuclear chemistry; Chemistry; Chemical engineering; Diesel fuel; Selectivity; Metallurgy; Organic chemistry; Ceramic; Combustion; Composite material","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":[0.002509416,0.0002153587,0.0004233984,0.00008717736,0.0002670918,0.00005974014,0.0009007133,0.00007499984,0.00007606878],"category_scores_gemma":[0.0001715445,0.0001585997,0.00008090113,0.00008567078,0.00044025,0.000343684,0.0002499343,0.00006495379,0.00005353376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001301976,"about_ca_system_score_gemma":0.00002309297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006214352,"about_ca_topic_score_gemma":0.00001477177,"domain_scores_codex":[0.9982538,0.00005571105,0.0005033429,0.0004752167,0.0004511769,0.0002607518],"domain_scores_gemma":[0.9977433,0.0004481079,0.000679342,0.001080941,0.00001059215,0.00003773643],"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":[0.0003551735,0.00008175984,0.0005766713,0.0001287814,0.00001292848,2.247103e-7,0.0003027518,0.001065609,0.9951618,0.0001554257,0.00002055389,0.00213837],"study_design_scores_gemma":[0.0005998717,0.0002878538,0.003649479,0.00002675108,0.0000765262,0.000001729422,0.00005721182,0.001947352,0.9931253,0.00005605853,0.00002297701,0.0001489559],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979109,0.00001775533,0.0007121604,0.00003865128,0.0001190986,0.0008291077,0.00007360171,0.00001229266,0.0002865019],"genre_scores_gemma":[0.9983172,0.00001506926,0.001088272,0.00001248588,0.00003660379,0.0003583061,0.0001148918,0.00001700625,0.00004010504],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003072808,"threshold_uncertainty_score":0.6467506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007639251385683243,"score_gpt":0.2739353721699954,"score_spread":0.2662961207843122,"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."}}