{"id":"W48136906","doi":"10.2166/wqrj.2003.010","title":"Characterization of Particles in Slow Sand Filtration at North Caribou Water Treatment Plant","year":2003,"lang":"en","type":"article","venue":"Water Quality Research Journal","topic":"Fecal contamination and water quality","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Turbidity; Clogging; Filtration (mathematics); Sand filter; Filter (signal processing); Slow sand filter; Raw water; Effluent; Particle (ecology); Environmental science; Particle size; Environmental engineering; Outflow; Water treatment; Particle counter; Particle-size distribution; Pilot plant; Characterization (materials science); Pulp and paper industry; Materials science; Chemistry; Wastewater; Geology; Nanotechnology; Aerosol; Oceanography; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.003868934,0.0001130234,0.0001900713,0.00009266931,0.0002528986,0.00007672345,0.0001290442,0.00005847332,0.001858312],"category_scores_gemma":[0.00006423115,0.00006337134,0.00007125411,0.0001232053,0.0001749564,0.0004370334,0.0000696676,0.0001978586,0.0002048896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005906512,"about_ca_system_score_gemma":0.00001853065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007627259,"about_ca_topic_score_gemma":0.001472505,"domain_scores_codex":[0.9960494,0.001918041,0.0005635208,0.0002197775,0.0007370247,0.0005122073],"domain_scores_gemma":[0.9994873,0.0000558359,0.00006190382,0.0001820533,0.00004677935,0.0001661056],"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":[0.0001185724,0.0002411825,0.2360062,0.00001258239,0.00001163388,0.00001562563,0.005576584,0.00005370455,0.7567945,0.00007331718,0.00004542153,0.001050738],"study_design_scores_gemma":[0.0006427958,0.0001548244,0.2407523,0.000007775158,0.000003065345,0.00001554157,0.00009107417,0.00007218642,0.7541147,0.0004021116,0.003657647,0.00008599483],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983751,0.000004784118,0.00008068928,0.0008108705,0.00005736896,0.0002169469,0.00003040585,0.000006488,0.000417379],"genre_scores_gemma":[0.9986356,0.00003579001,0.00004355302,0.00005159211,0.00002396855,0.00001601609,0.0001456686,0.0000075597,0.001040252],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00548551,"threshold_uncertainty_score":0.9990541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1133977165312612,"score_gpt":0.3442313036093877,"score_spread":0.2308335870781265,"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."}}