{"id":"W2794247826","doi":"10.1016/j.biortech.2018.01.082","title":"Bioflocculants’ production from a cellulase-free xylanase-producing Pseudomonas boreopolis G22 by degrading biomass and its application in cost-effective harvest of microalgae","year":2018,"lang":"en","type":"article","venue":"Bioresource Technology","topic":"Coagulation and Flocculation Studies","field":"Environmental Science","cited_by":45,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lakehead University","funders":"Natural Sciences and Engineering Research Council of Canada; China Scholarship Council","keywords":"Biomass (ecology); Xylanase; Cellulase; Chemistry; Fermentation; Food science; Xylose; Hydrolysis; Hemicellulose; Pseudomonas; Yield (engineering); Flocculation; Cellulose; Pulp and paper industry; Bacteria; Biochemistry; Biology; Agronomy; Organic chemistry; Materials science; Enzyme","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":[0.0002073465,0.0001665278,0.0002256281,0.0002640914,0.0001439054,0.00001071716,0.0002162182,0.0001680738,0.00004142863],"category_scores_gemma":[0.0001978676,0.0001637587,0.00002595247,0.0009068268,0.000611082,0.00009131442,0.0003027759,0.0001052876,0.00004515978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001228618,"about_ca_system_score_gemma":0.000004523778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002066871,"about_ca_topic_score_gemma":0.001065253,"domain_scores_codex":[0.9986886,0.00004913565,0.0002868258,0.0005931341,0.0001528942,0.0002293556],"domain_scores_gemma":[0.9992629,0.00004326173,0.0001831096,0.0004379715,0.00002939898,0.00004333161],"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":[0.00002747432,0.00005468311,0.4009006,0.000007182257,0.00001232188,7.111497e-7,0.0003807564,0.000007062872,0.5785739,0.00008822613,0.0007840883,0.01916297],"study_design_scores_gemma":[0.0006222704,0.00007837547,0.3772656,0.00002595822,0.00002176688,0.000006879474,0.0003507374,0.002011159,0.609304,0.00054693,0.009539965,0.0002263142],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959937,0.000480585,0.001181352,0.0008666502,0.00005723158,0.001065538,0.00007303512,0.0001255992,0.0001563436],"genre_scores_gemma":[0.9990214,0.00002066443,0.0005956119,0.00002985479,0.00004490393,0.0001692223,0.00003953755,0.00001537762,0.00006339294],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03073008,"threshold_uncertainty_score":0.6677885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01086368744168326,"score_gpt":0.2354716647203014,"score_spread":0.2246079772786181,"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."}}