{"id":"W3168351178","doi":"10.3390/w13111564","title":"Woven-Fiber Microfiltration (WFMF) and Ultraviolet Light Emitting Diodes (UV LEDs) for Treating Wastewater and Septic Tank Effluent","year":2021,"lang":"en","type":"article","venue":"Water","topic":"Water Quality Monitoring Technologies","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Asian Institute of Technology; Thailand Institute of Scientific and Technological Research; National Institute of Metrology, China; Bill and Melinda Gates Foundation; U.S. Department of State","keywords":"Wastewater; Septic tank; Effluent; Environmental science; Microfiltration; Coliphage; Turbidity; Kjeldahl method; Environmental engineering; Pulp and paper industry; Greywater; Waste management; Chemistry; Bacteriophage; Membrane; Biology; Engineering; Nitrogen; Escherichia coli; Ecology","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":[0.0002290636,0.0004050288,0.0002284398,0.000178392,0.000182637,0.0003188468,0.0002678562,0.0003617858,0.0003665745],"category_scores_gemma":[0.0001968788,0.0001689776,0.0005408417,0.000348655,0.0001775239,0.0003215941,0.0001987915,0.0003901387,0.00009474227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005207984,"about_ca_system_score_gemma":0.0004384993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005736759,"about_ca_topic_score_gemma":0.01000772,"domain_scores_codex":[0.9998397,0.00003406737,0.000007413299,0.0000491374,0.00005211166,0.00001761707],"domain_scores_gemma":[0.9999003,0.00003398,0.00003672629,0.000007853004,0.00001563612,0.000005481339],"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":[0.0001535671,0.0003416977,0.01516925,0.0005419955,0.00009771017,0.0001769637,0.0001124292,0.1637913,0.7331302,0.001738206,0.0002874333,0.08445922],"study_design_scores_gemma":[0.00003365657,0.001246124,0.02130297,0.00002372744,0.00009931114,0.0002350225,0.000109186,0.4322358,0.5373625,0.0007628204,0.00654233,0.00004665285],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8794034,0.001086536,0.117103,0.00008834228,0.00002485986,0.00005851221,0.0001798405,0.0001817946,0.001873655],"genre_scores_gemma":[0.9649344,0.000889909,0.03159652,0.00002425066,0.000006900676,0.0000497097,0.0001301976,0.00001273336,0.002355355],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005736759,"threshold_uncertainty_score":0.01140678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01360130912213665,"score_gpt":0.2350993098605712,"score_spread":0.2214980007384345,"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."}}