{"id":"W4316923292","doi":"10.3808/jeil.202200092","title":"Strategies for Mitigating MBR Membrane Biofouling","year":2022,"lang":"en","type":"article","venue":"Journal of Environmental Informatics Letters","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Biofouling; Extracellular polymeric substance; Membrane; Membrane bioreactor; Wastewater; Reuse; Membrane fouling; Sewage treatment; Chemistry; Bioreactor; Pulp and paper industry; Biochemical engineering; Environmental science; Environmental engineering; Waste management; Fouling; Bacteria; Biofilm; Engineering; Biology; Biochemistry; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005900635,0.0001474991,0.0002032961,0.0001039611,0.0003473237,0.00006389218,0.0004643959,0.00003375511,0.001710866],"category_scores_gemma":[0.00002412766,0.0001400963,0.0001428752,0.0001165102,0.0001943468,0.0009728994,0.0002902607,0.0003215645,0.00003555009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003693104,"about_ca_system_score_gemma":0.00001212877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003000934,"about_ca_topic_score_gemma":5.897249e-7,"domain_scores_codex":[0.9982287,0.0000340329,0.0008110869,0.00007747261,0.0005939299,0.0002547623],"domain_scores_gemma":[0.9988729,0.00009501196,0.0007983596,0.0001677191,0.000002108532,0.00006394218],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006567068,0.0001067747,0.001856145,0.00004164,0.00005809115,0.00001321629,0.003768025,0.2526297,0.7275754,0.0001953138,0.009467104,0.004222879],"study_design_scores_gemma":[0.009377247,0.003550275,0.008306047,0.0001072199,0.0003602039,0.002313804,0.2289791,0.07806444,0.3177367,0.004680337,0.343769,0.002755632],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914268,0.00002557508,0.005860647,0.001003808,0.0002298332,0.0002378168,0.00003719568,0.00002518112,0.001153111],"genre_scores_gemma":[0.9720166,0.00001893434,0.02552631,0.002303873,0.0000387393,0.00002107376,0.00001152959,0.00001583952,0.00004709118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4098387,"threshold_uncertainty_score":0.9992017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01221738666600656,"score_gpt":0.2250395942723343,"score_spread":0.2128222076063277,"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."}}