{"id":"W4388924298","doi":"10.1016/j.biortech.2023.130084","title":"Functional screening pipeline to uncover laccase-like multicopper oxidase enzymes that transform industrial lignins","year":2023,"lang":"en","type":"article","venue":"Bioresource Technology","topic":"Enzyme-mediated dye degradation","field":"Agricultural and Biological Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto; Concordia University; Genome Canada","keywords":"Laccase; Lignin; Multicopper oxidase; Enzyme; Chemistry; Biochemistry; 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":[0.0008776861,0.001462149,0.001182572,0.001314195,0.000326844,0.0008034935,0.0004886735,0.0005193719,0.001627778],"category_scores_gemma":[0.0008699119,0.0003032025,0.0009571302,0.0007337707,0.0002098947,0.0004009754,0.0007198965,0.0006869897,0.001187884],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003529401,"about_ca_system_score_gemma":0.0007665795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007151796,"about_ca_topic_score_gemma":0.001098121,"domain_scores_codex":[0.9992994,0.00007505986,0.00004909792,0.0001646286,0.0002981946,0.0001136942],"domain_scores_gemma":[0.9996843,0.00007376468,0.00005153452,0.00003547229,0.0001010918,0.00005388768],"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":[0.0001803991,0.0002751508,0.001213318,0.0001503337,0.00003199001,0.0001433421,0.00003263845,0.0006394233,0.9836738,0.0001168999,0.0002862513,0.01325647],"study_design_scores_gemma":[0.00005180866,0.001426452,0.008940885,0.0000255512,0.0001343494,0.0005295506,0.0000703918,0.009367644,0.973256,0.0001889873,0.005968092,0.00004025899],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8441845,0.002714367,0.1261112,0.0006325866,0.0001111501,0.002113371,0.01435151,0.004570882,0.005210602],"genre_scores_gemma":[0.8308779,0.001953591,0.1339543,0.0003275662,0.00002509489,0.001175182,0.02468256,0.0002885247,0.006715429],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001627778,"threshold_uncertainty_score":0.005445421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06054376713708822,"score_gpt":0.2348595207905674,"score_spread":0.1743157536534792,"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."}}