{"id":"W4288046873","doi":"10.1098/rsos.220078","title":"Insights into selective hydrogenation of levulinic acid using copper on manganese oxide octahedral molecular sieves","year":2022,"lang":"en","type":"article","venue":"Royal Society Open Science","topic":"Catalysis for Biomass Conversion","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; UK Catalysis Hub; Tezpur University; Queen's University; Queen's University Belfast","keywords":"Levulinic acid; Catalysis; Copper; Inorganic chemistry; Materials science; Selectivity; Molecular sieve; Leaching (pedology); Inductively coupled plasma; Nuclear chemistry; Chemistry; Organic chemistry; Metallurgy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004854824,0.0001300466,0.0001748608,0.00008172118,0.0004777587,0.00007267509,0.001020444,0.0000396175,0.00003682844],"category_scores_gemma":[0.00003533673,0.0001367041,0.0001379149,0.001262061,0.0001972646,0.0003412233,0.0007750499,0.0001684122,0.00001084406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007369982,"about_ca_system_score_gemma":0.0001388504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002732897,"about_ca_topic_score_gemma":0.00001126589,"domain_scores_codex":[0.9984862,0.00003764851,0.000202232,0.0003573978,0.0006903126,0.0002262492],"domain_scores_gemma":[0.9994487,0.00002787077,0.00007390714,0.0002887981,0.00008433207,0.00007642045],"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":[0.000008348669,0.00003061838,0.0002058374,0.00001124978,0.0000282019,0.000002737637,0.002090144,0.1507148,0.846345,0.0001124676,0.0002401127,0.0002105126],"study_design_scores_gemma":[0.0002258819,0.00005745102,0.0008415268,0.00000801579,0.0000161663,0.000001985993,0.0007810877,0.3493108,0.6482837,0.000131536,0.0001844595,0.0001574023],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977282,0.0001274565,0.0008372714,0.00003721594,0.0001365107,0.0002591261,0.00000487446,0.00004636162,0.0008230258],"genre_scores_gemma":[0.9975837,0.000002602805,0.002205634,0.0001129817,0.000008526789,0.00001656184,0.00001212975,0.00001676669,0.0000410444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.198596,"threshold_uncertainty_score":0.557463,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01133303815352489,"score_gpt":0.2567672602609412,"score_spread":0.2454342221074163,"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."}}