{"id":"W4410912081","doi":"10.18331/brj2025.12.2.3","title":"Biochar-supported highly dispersed ultrasmall Cu/ZnO nanoparticles as a highly efficient novel catalyst for CO2 hydrogenation to methanol","year":2025,"lang":"en","type":"article","venue":"Biofuel Research Journal","topic":"Catalysts for Methane Reforming","field":"Chemical Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Regional Development Fund; Generalitat de Catalunya; European Commission; Ministerio de Ciencia e Innovación; Institut Català de Nanociència i Nanotecnologia","keywords":"Biochar; Catalysis; Methanol; Nanoparticle; Materials science; Chemical engineering; Nanotechnology; Chemistry; Organic chemistry; Pyrolysis","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":[0.0001121862,0.0003273083,0.0002379586,0.0002241375,0.0001196976,0.0003129543,0.0004575337,0.0003175303,0.0002693173],"category_scores_gemma":[0.000170302,0.0001893775,0.0002120944,0.0001847953,0.0002035756,0.0002780559,0.0002348676,0.0002941298,0.0001671565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003376901,"about_ca_system_score_gemma":0.000153291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001242832,"about_ca_topic_score_gemma":0.003284517,"domain_scores_codex":[0.9998719,0.000009531452,0.00001032107,0.00003446881,0.0000454421,0.00002833948],"domain_scores_gemma":[0.999952,0.000007126225,0.00001245136,0.000005519991,0.00001172077,0.00001133218],"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":[0.00002835041,0.00001212106,0.00013391,0.0000452483,0.000005411999,0.00005573661,0.000008621931,0.0001907202,0.996972,0.000103914,0.00005265675,0.002391258],"study_design_scores_gemma":[0.000005538999,0.00004015313,0.0006571784,0.000002287222,0.0000100153,0.00005899432,0.0000135514,0.00296192,0.9952166,0.0000286569,0.001000382,0.000004671967],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9766783,0.002890807,0.01740568,0.0001528515,0.0001377379,0.00003061611,0.0002308009,0.0002113126,0.002261858],"genre_scores_gemma":[0.994709,0.0005222387,0.00410472,0.00001652743,0.000009836194,0.000007766725,0.00008097946,0.00001304946,0.0005358433],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001242832,"threshold_uncertainty_score":0.002471149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04333837257890409,"score_gpt":0.3492570126249834,"score_spread":0.3059186400460793,"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."}}