{"id":"W4319065309","doi":"10.1016/j.fuel.2023.127648","title":"Radial flow tubular membrane bioreactor for enhanced enzymatic hydrolysis of lignocellulosic waste biomass","year":2023,"lang":"en","type":"article","venue":"Fuel","topic":"Biofuel production and bioconversion","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"United Arab Emirates University","keywords":"Bioreactor; Substrate (aquarium); Lignocellulosic biomass; Biomass (ecology); Membrane bioreactor; Chemistry; Membrane reactor; Product inhibition; Hydrolysis; Enzymatic hydrolysis; Chromatography; Biofuel; Pulp and paper industry; Yield (engineering); Membrane; Chemical engineering; Materials science; Biochemistry; Enzyme; Biotechnology; Organic chemistry; Agronomy; Non-competitive inhibition; Biology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001350107,0.0001323898,0.0002040712,0.0001926691,0.00003046816,0.00001166012,0.0001172763,0.0001070177,0.00011068],"category_scores_gemma":[0.00002704021,0.0001230061,0.0001283302,0.0004279921,0.00003095796,0.00007311653,0.00001948769,0.00005673813,0.0001767254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002484733,"about_ca_system_score_gemma":0.000009878822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004830152,"about_ca_topic_score_gemma":0.000001047628,"domain_scores_codex":[0.9992432,0.00001193494,0.000221791,0.0001773487,0.0001314127,0.0002142859],"domain_scores_gemma":[0.999607,0.00003811576,0.000037065,0.0002235169,0.0000326722,0.00006165757],"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":[0.00001906244,0.00001691627,0.000005752991,0.001346514,0.00006331153,9.752321e-7,0.0002158627,0.0004365577,0.993435,0.000006011046,0.003213736,0.001240349],"study_design_scores_gemma":[0.0004954261,0.00004576157,0.00002230399,0.00002394741,0.00003829063,8.077832e-7,0.0000937228,0.07361359,0.9190794,0.00007971869,0.006366964,0.0001401313],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935184,0.0004799782,0.001980084,0.0003239607,0.001851276,0.0004769641,0.00008829897,0.0005906982,0.0006903196],"genre_scores_gemma":[0.998345,0.0001522757,0.0006525442,0.00001396329,0.0002998449,0.0000285716,0.00009236398,0.00003133622,0.0003840538],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07435562,"threshold_uncertainty_score":0.5016044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01169069397150973,"score_gpt":0.2041375658026764,"score_spread":0.1924468718311667,"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."}}