{"id":"W3093141549","doi":"10.1039/d0gc02782k","title":"Electrocatalytic hydrogenation and depolymerization pathways for lignin valorization: toward mild synthesis of chemicals and fuels from biomass","year":2020,"lang":"en","type":"article","venue":"Green Chemistry","topic":"Lignin and Wood Chemistry","field":"Engineering","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver Biotech (Canada); University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Korea Institute of Science and Technology","keywords":"Biorefinery; Depolymerization; Lignin; Biomass (ecology); Renewable energy; Chemistry; Pulp and paper industry; Biofuel; Sustainable production; Organic chemistry; Production (economics); Waste management; Raw material","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":[],"consensus_categories":[],"category_scores_codex":[0.00002266237,0.000152794,0.0002025791,0.00001023448,0.00002554125,0.00001766245,0.00008845211,0.0001498087,0.000005373956],"category_scores_gemma":[0.00005341938,0.0001719373,0.00003748933,0.0001139172,0.00003747329,0.00006765418,0.00002857746,0.00005530014,5.366112e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001341015,"about_ca_system_score_gemma":0.00001525651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005542407,"about_ca_topic_score_gemma":1.099711e-7,"domain_scores_codex":[0.9992983,0.00000289973,0.0002255865,0.0002306474,0.0001026973,0.0001398192],"domain_scores_gemma":[0.9996188,0.00008245861,0.00005737222,0.0001057794,0.00002252539,0.0001130564],"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":[0.000006426872,0.000006721923,0.0003304929,0.0009488585,0.00005892762,5.533703e-7,0.0001672449,0.000002834907,0.9976341,0.000003390785,0.0001165625,0.0007239105],"study_design_scores_gemma":[0.0002881349,0.000007895003,0.00001870681,0.00004491209,0.00006410947,0.000002324729,0.00005362025,0.00451801,0.994691,0.0001106967,0.00002578558,0.0001747741],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954929,0.001244846,0.001766695,0.0002253074,0.0000185316,0.0001200144,0.0001994652,0.0001506151,0.0007816395],"genre_scores_gemma":[0.9988165,0.00009445837,0.0005694974,0.00002683338,0.0001853613,0.0000336278,0.0002382524,0.00003051997,0.000004927598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004515175,"threshold_uncertainty_score":0.7011399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01509013565193048,"score_gpt":0.1870216760246508,"score_spread":0.1719315403727203,"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."}}