{"id":"W2784492610","doi":"10.1021/acs.iecr.7b04582","title":"Metal Oxide-Based Catalysts for the Autothermal Reforming of Glycerol","year":2018,"lang":"en","type":"article","venue":"Industrial & Engineering Chemistry Research","topic":"Catalysts for Methane Reforming","field":"Chemical Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation; Faculty of Graduate Studies and Research, University of Regina","keywords":"Glycerol; Catalysis; Chemistry; Catalytic reforming; Methane reformer; Dilution; Hydrogen; Metal; Selectivity; Steam reforming; Oxide; Oxygen; Hydrogen production; Chemical engineering; Inorganic chemistry; Nuclear chemistry; Organic chemistry","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":[0.00009263439,0.0002579134,0.0001952101,0.0001758197,0.00009769174,0.0003039081,0.0004452927,0.0002043475,0.0004253253],"category_scores_gemma":[0.0001042596,0.000123237,0.0002408244,0.0001229917,0.0001231671,0.0002888013,0.0001786825,0.000301729,0.0002393973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002580473,"about_ca_system_score_gemma":0.000153476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000977722,"about_ca_topic_score_gemma":0.003046289,"domain_scores_codex":[0.9999048,0.00001061635,0.000005457537,0.00001382274,0.00004640667,0.00001899748],"domain_scores_gemma":[0.9999791,0.000004277982,0.000005232789,0.000002291161,0.000005912676,0.000003145333],"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":[0.00004701739,0.00001454716,0.0001605875,0.0001283141,0.000009745924,0.00006183303,0.00001316952,0.0002483075,0.9961001,0.0002366226,0.00002505429,0.002954754],"study_design_scores_gemma":[0.000002976327,0.00004404151,0.0003408731,0.000003635477,0.000009259509,0.00005264393,0.00001761335,0.001195641,0.9965656,0.00002278959,0.001742039,0.000002891434],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9759368,0.007423628,0.01324973,0.0001215794,0.0000570997,0.0000509203,0.0001268514,0.000117278,0.002916053],"genre_scores_gemma":[0.9922304,0.002099113,0.004217533,0.00001744958,0.000006112239,0.00000697752,0.0000868486,0.00001202837,0.001323488],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000977722,"threshold_uncertainty_score":0.001944005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.101188598428124,"score_gpt":0.347775545355907,"score_spread":0.246586946927783,"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."}}