{"id":"W2982443025","doi":"10.1002/aws2.1160","title":"Sedimentation: Hydraulic improvement of drinking water biofiltration","year":2019,"lang":"en","type":"article","venue":"AWWA Water Science","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Water Research Foundation","keywords":"Sedimentation; Backwashing; Biofilter; Environmental science; Hydraulic head; Filter (signal processing); Effluent; Water treatment; Environmental engineering; Engineering; Geology; Sediment; Geotechnical 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":["insufficient_payload"],"category_scores_codex":[0.0005928525,0.0001203318,0.0001055654,0.0001038172,0.0001950102,0.0000680443,0.0005252807,0.00002505606,0.002777586],"category_scores_gemma":[0.000002260443,0.00007601598,0.00003848823,0.0002817542,0.0004037358,0.001188964,0.0005532204,0.00005555268,0.003395422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001789909,"about_ca_system_score_gemma":0.000007879519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002468867,"about_ca_topic_score_gemma":0.00001941037,"domain_scores_codex":[0.9981173,0.00001375946,0.0002671291,0.0004424993,0.0006886455,0.0004706802],"domain_scores_gemma":[0.9994242,0.000005725228,0.00005198385,0.000429262,0.00001767707,0.0000711402],"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":[0.000002838008,0.00003483684,0.03540954,0.000005835475,0.000004326302,6.274096e-7,0.001577131,0.0007799317,0.960901,0.00008092753,0.000145907,0.001057081],"study_design_scores_gemma":[0.0002248275,0.0001197486,0.01836963,0.00000601553,0.00001152286,0.000001438825,0.0001274834,0.001046246,0.9748515,0.0003060198,0.004781929,0.0001536715],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9755999,0.000002051251,0.0008552429,0.0005721732,0.0004199958,0.0003686319,7.320155e-7,0.00004163609,0.02213965],"genre_scores_gemma":[0.9952092,0.000001155542,0.0008728243,0.0003136165,0.00001919906,0.00001902174,0.000009750833,0.000007817011,0.003547424],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0196093,"threshold_uncertainty_score":0.998134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007726319859192344,"score_gpt":0.2056578631695159,"score_spread":0.1979315433103235,"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."}}