{"id":"W4243726266","doi":"10.32920/ryerson.14648316","title":"Characterization of microbial aggregates in relation to membrane biofouling in submerged membrane bioreactors","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Biofouling; Membrane bioreactor; Membrane; Extracellular polymeric substance; Chemistry; Microfiltration; Permeation; Bioreactor; Chromatography; Ultrafiltration (renal); Chemical engineering; Biofilm; Bacteria; Biochemistry; Biology; Organic chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003420812,0.0003462271,0.0004441809,0.0003926503,0.000251546,0.0005156172,0.0001644085,0.0003875853,0.0001758478],"category_scores_gemma":[0.0004075197,0.0001311593,0.0003377564,0.0003060884,0.0001550356,0.0004295101,0.0003197695,0.0004105778,0.0001181792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001677066,"about_ca_system_score_gemma":0.000158762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001049068,"about_ca_topic_score_gemma":0.0008648188,"domain_scores_codex":[0.9996747,0.00004567904,0.00003434081,0.00007510874,0.0001184744,0.00005180123],"domain_scores_gemma":[0.9996947,0.00006858335,0.00008983802,0.00001751542,0.00009340919,0.0000359453],"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":[0.00003077989,0.00001154866,0.001152075,0.00001981852,0.000003968319,0.00003209212,0.00003501563,0.00005962378,0.9977701,0.000005166116,0.000002706579,0.0008771382],"study_design_scores_gemma":[0.000004429806,0.0003470909,0.03090861,0.000009978668,0.00002671885,0.000157076,0.000228874,0.001914826,0.9660667,0.000034715,0.0002906729,0.00001037563],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950944,0.0004835125,0.004047563,0.00001882753,0.000005194956,0.00003033549,0.00011493,0.00001646072,0.0001886872],"genre_scores_gemma":[0.9932829,0.0004998004,0.005471082,0.00002868355,0.000008404479,0.00005160007,0.0002093659,0.0000116902,0.00043647],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001049068,"threshold_uncertainty_score":0.002085865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0153709705483092,"score_gpt":0.2356688545190385,"score_spread":0.2202978839707293,"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."}}