{"id":"W231368615","doi":"10.1023/a:1005240000042","title":"Nutrient Retention in a Northern Prairie Marsh (Frank Lake, Alberta) Receiving Municipal and Agro-Industrial Wastewater","year":2001,"lang":"en","type":"article","venue":"Water Air & Soil Pollution","topic":"Coastal wetland ecosystem dynamics","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Marsh; Eutrophication; Environmental science; Wetland; Hydrology (agriculture); Water quality; Phosphorus; Nutrient; Sediment; Wastewater; Environmental engineering; Ecology; Chemistry; Geology; Biology; Geomorphology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001350497,0.0001699623,0.0002191414,0.0003289388,0.002340091,0.000723761,0.0005757813,0.0004342344,0.0005724385],"category_scores_gemma":[0.0002768436,0.0001887868,0.0001428644,0.0006073881,0.0009441836,0.000197135,0.0004725343,0.0003446599,0.000127935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004444354,"about_ca_system_score_gemma":0.003736907,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8770722,"about_ca_topic_score_gemma":0.9446169,"domain_scores_codex":[0.9999096,0.000008283617,0.000002820012,0.00001787256,0.00002470544,0.00003662059],"domain_scores_gemma":[0.9998475,0.00001663213,0.0000171698,0.00000498942,0.00006155494,0.00005212171],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005352233,0.0009590948,0.8694114,0.000113386,0.00007769975,0.005646511,0.01308636,0.001738582,0.0809733,0.0005538954,0.001441924,0.02064557],"study_design_scores_gemma":[0.00002936667,0.0003720522,0.9882365,0.000006791831,0.00002654577,0.0004268114,0.006362821,0.001281079,0.002297431,0.00009296068,0.0008536432,0.00001395474],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996291,0.00001348845,0.00001770025,0.00001475955,9.875146e-7,0.000003648044,0.00002894309,0.000001055544,0.0002902368],"genre_scores_gemma":[0.998059,0.00003898466,0.00009436967,0.00002358409,9.490657e-7,0.000003731286,0.00008751655,0.00000138838,0.001690416],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1229278,"threshold_uncertainty_score":0.2473034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01159948653434399,"score_gpt":0.1938058046988083,"score_spread":0.1822063181644644,"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."}}