{"id":"W2010569772","doi":"10.1038/sj.jim.7000150","title":"Enzyme treatment to reduce solids and improve settling of sewage sludge","year":2001,"lang":"en","type":"article","venue":"Journal of Industrial Microbiology & Biotechnology","topic":"Biofuel production and bioconversion","field":"Engineering","cited_by":93,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Cellulase; Lipase; Settling; Protease; Chemistry; Sewage sludge; Enzyme; Food science; Suspended solids; Sewage treatment; Activated sludge; Chromatography; Pulp and paper industry; Wastewater; Biochemistry; Environmental engineering; Environmental science","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":[0.0002249297,0.0001753794,0.0004201219,0.0004297643,0.00003785846,0.000007006064,0.0001700948,0.0009622514,0.000035242],"category_scores_gemma":[0.0000596622,0.0001394508,0.00008588067,0.0002456198,0.0001711605,0.00005326122,0.00005563536,0.0004786699,0.000008838829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001260988,"about_ca_system_score_gemma":0.00004500944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001304779,"about_ca_topic_score_gemma":0.000002286846,"domain_scores_codex":[0.9989949,0.00003963029,0.0005092434,0.0001712478,0.00003050985,0.0002544751],"domain_scores_gemma":[0.9994763,0.00002818465,0.0001881315,0.0001689792,0.00006307666,0.00007533831],"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":[0.0001612878,0.00003988589,0.0001662699,0.000007997891,0.0001060045,0.00001841114,0.00005069179,0.00005425273,0.963409,0.00001670618,0.00211997,0.0338495],"study_design_scores_gemma":[0.0013693,0.001245765,0.00001549747,0.00002807149,0.00004063555,0.001069056,0.0001627417,0.0000154393,0.8651547,0.0000198227,0.1307647,0.0001142351],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928468,0.0008393864,0.0001843382,0.004327943,0.001493855,0.0001813849,0.00002545748,0.00005912086,0.00004166065],"genre_scores_gemma":[0.9975813,0.001059211,0.0007200299,0.00008090078,0.0004618259,0.000001530628,0.000003840395,0.00001525648,0.00007610663],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1286448,"threshold_uncertainty_score":0.7421764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02043766635587369,"score_gpt":0.2303577148378838,"score_spread":0.2099200484820101,"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."}}