{"id":"W3142882166","doi":"","title":"Assessment of Ultrafiltration Membrane Ageing in Full-scale Water Treatment Facilities","year":2021,"lang":"en","type":"dissertation","venue":"TSpace","topic":"Membrane Separation Technologies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Ultrafiltration (renal); Ageing; Scale (ratio); Full scale; Water treatment; Environmental science; Medicine; Chemistry; Engineering; Environmental engineering; Chromatography; Geography; Cartography; Internal medicine; Electrical engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001222268,0.0002571649,0.0003894894,0.000108017,0.00005358947,0.00003016414,0.0001693607,0.0002465097,0.005944043],"category_scores_gemma":[0.00002043528,0.0002066447,0.00009190032,0.0001706002,0.00006848189,0.0001755658,0.00003034722,0.0001669183,0.00008051388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003913266,"about_ca_system_score_gemma":0.0000411253,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002397049,"about_ca_topic_score_gemma":0.01826394,"domain_scores_codex":[0.9984917,0.00007510032,0.0003841917,0.0004142784,0.0003827051,0.0002520472],"domain_scores_gemma":[0.9994006,0.00004053794,0.0001393673,0.000372439,0.00001496855,0.00003206003],"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":[0.00001874747,0.0001149272,0.0007363269,0.0001222376,0.00001782894,0.00001633105,0.01156919,0.002953834,0.9827064,0.00004374349,0.00005293598,0.001647522],"study_design_scores_gemma":[0.0003115944,0.0001451473,0.01979269,0.00006596762,0.00002425564,0.000002460777,0.0222548,0.0002266203,0.955215,0.00005388455,0.001665815,0.0002417594],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.935504,0.00006058296,0.00003301632,0.0001249474,0.0001582815,0.0003588858,0.000008561996,0.00006816444,0.06368358],"genre_scores_gemma":[0.9169047,0.0002392995,0.0009011727,0.000009046094,0.00001171754,0.0001140426,0.0009087616,0.00001894931,0.08089227],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02749137,"threshold_uncertainty_score":0.9996502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01691388849428162,"score_gpt":0.3108681764803815,"score_spread":0.2939542879860998,"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."}}