{"id":"W2946054052","doi":"10.1021/acscentsci.9b00221","title":"Dynamic and Functional Profiling of Xylan-Degrading Enzymes in <i>Aspergillus</i> Secretomes Using Activity-Based Probes","year":2019,"lang":"en","type":"article","venue":"ACS Central Science","topic":"Biofuel production and bioconversion","field":"Engineering","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"H2020 European Research Council; Biotechnology and Biological Sciences Research Council; Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; Diamond Light Source; Generalitat de Catalunya; Ministerio de Ciencia e Innovación; Agence Nationale de la Recherche; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Ministerio de Ciencia, Innovación y Universidades; Directorate for Biological Sciences; Agència de Gestió d'Ajuts Universitaris i de Recerca; Royal Society; Ministerio de Economía y Competitividad; Yorkshire Forward","keywords":"Enzyme; Aspergillus niger; Xylan; Glycoside hydrolase; Chemistry; Profiling (computer programming); Biochemistry; Computational biology; Biology; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001966872,0.00008244683,0.00009472273,0.0001392033,0.0000525312,0.00002464577,0.00007777222,0.00003775089,0.00001911833],"category_scores_gemma":[0.00001283071,0.00007307989,0.00001608537,0.0004441525,0.0001428286,0.0003511989,0.00002693559,0.00009717398,0.000002050632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001249257,"about_ca_system_score_gemma":0.00006237973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002775311,"about_ca_topic_score_gemma":0.000004435818,"domain_scores_codex":[0.9992339,0.000009909505,0.00009835246,0.0002075132,0.0001933206,0.0002569881],"domain_scores_gemma":[0.9997953,0.00001481753,0.00002668305,0.0000884021,0.00002300549,0.00005184819],"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":[0.000009445762,0.00001175879,0.05268435,0.0001307122,0.000001766479,3.889556e-7,0.00005909332,0.0118623,0.9343691,0.00009498277,0.000002479832,0.0007736637],"study_design_scores_gemma":[0.0001823664,0.00001506933,0.04272725,0.0000394957,0.000002208387,0.000003272455,0.00006692771,0.3064693,0.6503432,0.00001516219,0.00004507403,0.00009062032],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998589,0.0001910912,0.0004618587,0.00005180413,0.0004037147,0.0001630718,0.000002974593,0.00004344526,0.00009304285],"genre_scores_gemma":[0.9985573,0.00002132556,0.001372648,0.00001457962,0.00001226553,0.000001017011,0.000001875761,0.000005622237,0.00001339435],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.294607,"threshold_uncertainty_score":0.2980111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009957828874791446,"score_gpt":0.2104959873561411,"score_spread":0.2005381584813497,"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."}}