{"id":"W156627570","doi":"10.1023/a:1017506914063","title":"Nitrogen retention in wetlands, lakes and rivers","year":2001,"lang":"en","type":"article","venue":"Hydrobiologia","topic":"Constructed Wetlands for Wastewater Treatment","field":"Environmental Science","cited_by":441,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Denitrification; Nitrogen; Sedimentation; Wetland; Environmental science; Nitrogen cycle; Aquatic ecosystem; Ecology; Environmental chemistry; Reactive nitrogen; Hydrology (agriculture); Biology; Chemistry; Sediment; Geology","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":[],"consensus_categories":[],"category_scores_codex":[0.00007430925,0.00009093642,0.00009008707,0.00003212213,0.00004045428,0.00001041453,0.00006895,0.0000551648,0.0006809149],"category_scores_gemma":[0.000006802093,0.000070666,0.0000210923,0.000113211,0.0001189348,0.00007582724,0.00008717505,0.0000527259,0.000217437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007403843,"about_ca_system_score_gemma":0.000001867571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003076243,"about_ca_topic_score_gemma":0.000939369,"domain_scores_codex":[0.9994072,0.00003143411,0.0001050544,0.0002226783,0.00004785324,0.0001857881],"domain_scores_gemma":[0.9998056,0.00001340294,0.00002808345,0.0001108493,0.000001234586,0.00004082588],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001641129,0.00001844314,0.9817481,8.719942e-7,0.000004991766,0.00002784542,0.00007404749,0.00005710102,0.01404608,0.000008260933,0.0001047339,0.003893103],"study_design_scores_gemma":[0.001724685,0.0002038191,0.9852852,0.00002178036,0.00002280781,0.0002271349,0.0001609173,0.0009647298,0.002991983,0.003705568,0.004367388,0.000323949],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936128,0.00002726178,0.00001071497,0.00006874121,0.00003908745,0.0001158405,0.000005076799,0.00003429284,0.00608616],"genre_scores_gemma":[0.999207,0.00005393522,0.0003221015,0.00002590544,0.000006911388,0.000008799151,0.00003037406,0.000004201295,0.0003408028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0110541,"threshold_uncertainty_score":0.7455541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009012049468311032,"score_gpt":0.1950119298728725,"score_spread":0.1859998804045614,"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."}}