{"id":"W172945119","doi":"10.2166/wqrj.2006.031","title":"Effectiveness of Vegetative Filter Strips in Removal of Sediments from Overland Flow","year":2006,"lang":"en","type":"article","venue":"Water Quality Research Journal","topic":"Soil erosion and sediment transport","field":"Agricultural and Biological Sciences","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Food and Agriculture; University of Guelph","keywords":"Surface runoff; Sediment; Filter (signal processing); Environmental science; Pollutant; Wetland; Hydrology (agriculture); Inflow; Vegetation (pathology); Environmental engineering; Geology; Geotechnical engineering; Geomorphology; Chemistry; Ecology; Oceanography","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.005266738,0.00008544764,0.0002622044,0.00004294917,0.00009823065,0.00002762366,0.0002140015,0.00007649714,0.0004429646],"category_scores_gemma":[0.00005035744,0.00002871137,0.0001216536,0.0002011876,0.0001320776,0.0001222477,0.00004049851,0.0003963031,0.000008284414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000418966,"about_ca_system_score_gemma":0.00001576065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004186946,"about_ca_topic_score_gemma":0.0003418866,"domain_scores_codex":[0.996341,0.001875812,0.0004632098,0.0001703222,0.0008383376,0.0003113377],"domain_scores_gemma":[0.9988864,0.0007017524,0.00006953916,0.00004848569,0.0002179529,0.00007584186],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0006055366,0.0002818934,0.1299042,0.00002916916,0.00002069151,0.00004300198,0.0003253791,0.00003164013,0.8670262,0.00004282124,0.00005749967,0.001631985],"study_design_scores_gemma":[0.0006716454,0.000186055,0.7302412,0.0001227675,0.000002869951,0.00000499445,0.0002125731,0.00002125037,0.2650639,0.003181142,0.0002341479,0.0000574617],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99895,0.000107686,0.000006563154,0.0001475287,0.00007108416,0.000138127,0.0000706376,0.000003883073,0.0005044674],"genre_scores_gemma":[0.9996102,0.00001909316,0.00008668212,0.000007519267,0.00009030662,0.000002216406,0.00008625364,6.879279e-7,0.0000970591],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6019623,"threshold_uncertainty_score":0.6329437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08675156884544222,"score_gpt":0.3452347800756778,"score_spread":0.2584832112302356,"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."}}