{"id":"W4225356295","doi":"10.1007/978-3-030-95786-5_9","title":"Nutrient Loading Impact on Remediation of Hydrocarbon Polluted Groundwater Using Constructed Wetland","year":2022,"lang":"en","type":"book-chapter","venue":"Earth and environmental sciences library","topic":"Constructed Wetlands for Wastewater Treatment","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Biostimulation; Bioremediation; Environmental remediation; Groundwater; Environmental science; Environmental engineering; Wetland; Groundwater pollution; Groundwater remediation; Water table; Constructed wetland; Pollutant; Pollution; Microcosm; Nutrient; Hydrocarbon; Environmental chemistry; Aquifer; Contamination; Sewage treatment; Chemistry; Ecology; Geology; Geotechnical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.00002564306,0.0001225321,0.0001154864,0.00009900176,0.0001221203,0.0002168587,0.0001656484,0.0001635692,0.001577769],"category_scores_gemma":[0.00002581785,0.00004807623,0.0001645494,0.0001470656,0.00006553559,0.0001521454,0.0001255808,0.0001022831,0.0002443066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002071336,"about_ca_system_score_gemma":0.0001945564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003232885,"about_ca_topic_score_gemma":0.007792811,"domain_scores_codex":[0.9999794,0.00000178349,7.16995e-7,0.000002729054,0.00001192952,0.000003484958],"domain_scores_gemma":[0.9999934,0.00000219525,6.992678e-7,3.962534e-7,0.000002448814,7.019002e-7],"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":[0.0004100555,0.0001667453,0.001441436,0.0004897651,0.00001692517,0.0006943428,0.0001521663,0.00541517,0.8391393,0.001822519,0.004125461,0.1461261],"study_design_scores_gemma":[0.00002642536,0.001147051,0.0159928,0.00006719631,0.00006905432,0.0005459664,0.0002714553,0.01309631,0.9220508,0.001083551,0.04562061,0.0000289204],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9452634,0.005738733,0.003104879,0.0002405289,0.0001089943,0.00002295135,0.0003427342,0.00009232738,0.04508552],"genre_scores_gemma":[0.8875439,0.006739173,0.00273782,0.0000809432,0.00001916147,0.00001448809,0.0003863603,0.00002762366,0.1024506],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003232885,"threshold_uncertainty_score":0.006428182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009346524619754335,"score_gpt":0.1878546873861891,"score_spread":0.1785081627664348,"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."}}