{"id":"W2985965608","doi":"10.1089/ees.2019.0209","title":"Biofouling of an Aerated Membrane Reactor: Four Distinct Microbial Communities","year":2019,"lang":"en","type":"article","venue":"Environmental Engineering Science","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University; Queen's University; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Queen's University","keywords":"Extracellular polymeric substance; Biofouling; Membrane; Biofilm; Membrane fouling; Microfiltration; Microbial population biology; Fouling; Aeration; Bioreactor; Chemistry; Compartment (ship); Pulp and paper industry; Chemical engineering; Bacteria; Biology; Biochemistry; Engineering","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000402822,0.0001892529,0.0001864879,0.0001117082,0.0001125216,0.00004141543,0.0008494852,0.00006601425,0.001591487],"category_scores_gemma":[0.00003056418,0.0001869812,0.00003922945,0.0003810022,0.0007704039,0.0007767781,0.0003974482,0.0001897184,0.0003879856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002264743,"about_ca_system_score_gemma":0.0000110522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001164324,"about_ca_topic_score_gemma":0.00001185956,"domain_scores_codex":[0.9985535,0.00002076405,0.0002649898,0.0003174284,0.0004849256,0.0003583644],"domain_scores_gemma":[0.9991445,0.00004691422,0.00009989928,0.0006112622,0.000002498309,0.00009493978],"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":[0.000006161508,0.00004558404,0.009829751,0.000008727985,0.000002608605,0.000001560863,0.0002853186,0.03268459,0.9565542,0.0000293408,0.000004584133,0.0005475999],"study_design_scores_gemma":[0.0002897274,0.0001465504,0.07511353,0.00002228261,0.000005961298,0.00002638693,0.0004478106,0.04883889,0.8741109,0.00001061457,0.0006639468,0.0003233398],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980062,0.000009628914,0.0002067366,0.00001925253,0.0001928083,0.0002089811,0.00001547094,0.0001490926,0.001191872],"genre_scores_gemma":[0.9956412,0.00000887615,0.004132401,0.00001943747,0.00001036618,0.000006232248,0.00001444762,0.00001876267,0.0001482833],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08244322,"threshold_uncertainty_score":0.9993212,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00878088743762921,"score_gpt":0.196148276114129,"score_spread":0.1873673886764998,"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."}}