{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002108526,0.0003183343,0.0004026593,0.0002485743,0.00007077058,0.00005880616,0.0001709345,0.0001501927,0.00003757745],"category_scores_gemma":[0.00004840056,0.0003767239,0.00007633211,0.0009088212,0.00002639848,0.0003881507,0.0002043615,0.0001907012,0.000002918926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004173202,"about_ca_system_score_gemma":0.00003491402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001301322,"about_ca_topic_score_gemma":0.000001704304,"domain_scores_codex":[0.9984052,0.000007296544,0.0003670684,0.000388406,0.0002232964,0.0006087183],"domain_scores_gemma":[0.9989468,0.00003396526,0.00006726599,0.0006250801,0.0001924014,0.0001345112],"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":[0.00001723539,0.0001471333,0.00117768,0.005034904,0.0004531521,0.003499453,0.003505504,0.05832633,0.9275439,0.00006962432,0.00011045,0.0001145989],"study_design_scores_gemma":[0.001308163,0.00009677924,0.00009560354,0.00003473159,0.0002710893,0.001723771,0.208187,0.01797149,0.7677785,0.00001152168,0.001857807,0.0006635563],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978369,0.0006722399,0.00007758453,0.000007647134,0.0000713168,0.0004870854,0.000002185036,0.0003077387,0.0005372932],"genre_scores_gemma":[0.9979446,0.00001571401,0.00005957807,5.967794e-7,0.00004670498,0.00005261579,0.00002556691,0.00007306439,0.00178155],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2046815,"threshold_uncertainty_score":0.9998685,"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."}}