{"id":"W4393976337","doi":"10.1016/j.apcata.2024.119727","title":"Structural study of mixed metal oxide catalysts comprising Mg, Ca, and Al used for upgrading biodiesel byproduct glycerol to glycerol carbonate","year":2024,"lang":"en","type":"article","venue":"Applied Catalysis A General","topic":"Carbon dioxide utilization in catalysis","field":"Chemical Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; University of Saskatchewan","keywords":"Glycerol; Catalysis; Chemistry; Biodiesel; Carbonate; Transesterification; Yield (engineering); Inorganic chemistry; Metal; Biodiesel production; Oxide; Heterogeneous catalysis; Nuclear chemistry; Chemical engineering; Organic chemistry; Materials science; 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":[0.00003850917,0.0001517354,0.0001032105,0.0001732122,0.0002100631,0.0001120562,0.0004033108,0.0001843757,0.001298459],"category_scores_gemma":[0.00009656254,0.000101424,0.0001353036,0.000158266,0.000187763,0.0001155461,0.0001044208,0.0001999158,0.00007895826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001964361,"about_ca_system_score_gemma":0.0001515412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002947764,"about_ca_topic_score_gemma":0.004024555,"domain_scores_codex":[0.999965,0.000002378128,0.000001456675,0.000007759121,0.00001333076,0.00001014952],"domain_scores_gemma":[0.9999764,0.000004951834,0.000006164403,0.000001881244,0.000006281677,0.000004262207],"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":[0.000589475,0.00004106709,0.001028912,0.0001928891,0.00002059775,0.0001993821,0.000111802,0.001261175,0.9918473,0.0007989532,0.0002497006,0.003658706],"study_design_scores_gemma":[0.00007191067,0.0007594705,0.01659433,0.00002290084,0.00008209958,0.0003320093,0.0006758717,0.01605596,0.9586907,0.0003565787,0.006332658,0.00002552115],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981616,0.0002245675,0.0002262243,0.00003396993,0.000008036925,0.000003333169,0.00007674767,0.000008829959,0.001256699],"genre_scores_gemma":[0.9992507,0.0000742371,0.0001349771,0.000007789629,0.000001759173,0.000002029991,0.00009256392,0.000002398822,0.0004335185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002947764,"threshold_uncertainty_score":0.005861223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01717651169490125,"score_gpt":0.2687281328546833,"score_spread":0.251551621159782,"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."}}