{"id":"W4367679317","doi":"10.1002/cjce.24927","title":"<scp> MnO <sub>x</sub> </scp> / <scp> CeO <sub>2</sub> </scp> catalysts for the low‐temperature selective catalytic reduction of <scp>NO</scp> with <scp> NH <sub>3</sub> </scp>","year":2023,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Catalytic Processes in Materials Science","field":"Materials Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Indian Institute of Technology (BHU) Varanasi; Banaras Hindu University","keywords":"X-ray photoelectron spectroscopy; Catalysis; Scanning electron microscope; Temperature-programmed reduction; Selectivity; Raman spectroscopy; Manganese; Hydrothermal circulation; Nanorod; Atmospheric temperature range; Transmission electron microscopy; Chemistry; Nuclear chemistry; Materials science; Chemical engineering; Nanotechnology; Organic chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009748198,0.000241605,0.0001756337,0.0001626125,0.0001065796,0.0001654801,0.0002065205,0.000179223,0.0004961953],"category_scores_gemma":[0.0001566335,0.0001367441,0.0001547616,0.0001156239,0.0001188693,0.0001495404,0.0001313923,0.0001731531,0.0001256848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002219116,"about_ca_system_score_gemma":0.0001839346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001603937,"about_ca_topic_score_gemma":0.004753404,"domain_scores_codex":[0.9999176,0.000005700736,0.00000554536,0.0000119173,0.00004655279,0.0000125794],"domain_scores_gemma":[0.9999418,0.000007808349,0.00001774095,0.000005885222,0.00001562626,0.00001115761],"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":[0.00003883511,0.00000669515,0.0002025183,0.00005512885,0.000005668656,0.00005777443,0.000005331439,0.0001453889,0.998428,0.00003483515,0.00006814422,0.0009517212],"study_design_scores_gemma":[0.000006952703,0.00004869498,0.002798172,0.000003303978,0.000009652753,0.0000942925,0.00001381189,0.001722144,0.9942933,0.00001077431,0.0009957099,0.000003102835],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954791,0.0005522198,0.002290286,0.00005504408,0.00002466165,0.00002034979,0.000194994,0.00006646007,0.001316821],"genre_scores_gemma":[0.995818,0.0003083572,0.002276716,0.00001643482,0.000003430685,0.00001177132,0.0001624226,0.00001642599,0.001386382],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001603937,"threshold_uncertainty_score":0.003189266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006576892973185783,"score_gpt":0.1955450168123766,"score_spread":0.1889681238391908,"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."}}