{"id":"W2945585512","doi":"10.1021/acssuschemeng.9b00811","title":"Carbonyl Reduction and Biomass: A Case Study of Sustainable Catalysis","year":2019,"lang":"en","type":"article","venue":"ACS Sustainable Chemistry & Engineering","topic":"Catalysis for Biomass Conversion","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Centre in Green Chemistry and Catalysis","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Biomass (ecology); Context (archaeology); Catalysis; Biochemical engineering; Benchmark (surveying); Green chemistry; Process engineering; Environmental science; Chemistry; Renewable energy; Waste management; Nanotechnology; Pulp and paper industry; Organic chemistry; Materials science; Engineering; Reaction mechanism; Ecology","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":[0.001021051,0.0006269006,0.0005566937,0.0009698184,0.001732484,0.001998442,0.001210047,0.002810179,0.002542896],"category_scores_gemma":[0.001047662,0.0001881478,0.000762929,0.001983444,0.001486737,0.001319383,0.001537837,0.0009941193,0.0005691783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001427207,"about_ca_system_score_gemma":0.0006016085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005532024,"about_ca_topic_score_gemma":0.009161395,"domain_scores_codex":[0.9990506,0.000337793,0.00002986654,0.00009804382,0.0003237164,0.0001600312],"domain_scores_gemma":[0.9993578,0.0003744409,0.00003125394,0.00004234937,0.0001071518,0.00008717641],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.001237153,0.003765709,0.03209403,0.004301896,0.0003090997,0.07374383,0.01095552,0.2794692,0.1097008,0.3390612,0.02397421,0.1213875],"study_design_scores_gemma":[0.0003420634,0.002659945,0.01854591,0.0007292684,0.0002672706,0.01137272,0.03001548,0.2454812,0.162694,0.08814892,0.4394786,0.0002645786],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9041753,0.005116876,0.02027189,0.002367945,0.0001756663,0.0002188481,0.0007863191,0.00009601534,0.06679115],"genre_scores_gemma":[0.9547746,0.004536692,0.02126161,0.0002027895,0.0000792616,0.000111826,0.0005197853,0.00005589273,0.0184576],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005532024,"threshold_uncertainty_score":0.01099968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002571890511944489,"score_gpt":0.1740132635580606,"score_spread":0.1714413730461161,"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."}}