{"id":"W3201996282","doi":"10.1111/gwmr.12483","title":"Artificial Sweeteners Identify Spatial Patterns of Historic Landfill Contaminated Groundwater Discharge in an Urban Stream","year":2021,"lang":"en","type":"article","venue":"Groundwater Monitoring & Remediation","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; McMaster University","funders":"Ministry of Environment; Government of Ontario; Environment and Climate Change Canada; McMaster University","keywords":"Leachate; Groundwater; Environmental science; STREAMS; MODFLOW; Hyporheic zone; Hydrology (agriculture); Contamination; Aquifer; Urban stream; Groundwater discharge; Environmental engineering; Baseflow; Plume; Groundwater flow; Surface water; Waste management; Geology; Drainage basin; Geography; Streamflow; Ecology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003400793,0.0002464509,0.0002707645,0.0001719017,0.0001305345,0.00009877433,0.0002647102,0.0001276465,0.0003847178],"category_scores_gemma":[0.00002854246,0.0002472216,0.00008023546,0.0003088991,0.00006534514,0.001049989,0.0002110735,0.0001882779,0.0001180957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001031646,"about_ca_system_score_gemma":0.0000160433,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007996342,"about_ca_topic_score_gemma":0.004184996,"domain_scores_codex":[0.9975166,0.0001902437,0.0006179643,0.0005667977,0.0006200209,0.0004884228],"domain_scores_gemma":[0.9991524,0.00002953758,0.0002014636,0.0004514386,0.00004530121,0.0001198572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002291945,0.0003497202,0.9128366,0.00002190214,0.00001733338,0.00002839438,0.002053133,0.0001694801,0.08187136,0.00002165545,0.00006871896,0.002538792],"study_design_scores_gemma":[0.0004301054,0.0001191765,0.9264545,0.00002876898,0.00004629158,0.000002017935,0.000338414,0.000299147,0.07101941,0.0001100061,0.0008608728,0.000291279],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923051,0.00002431901,0.005027621,0.00008015095,0.002080438,0.000256591,0.000009396465,0.00007606715,0.0001403377],"genre_scores_gemma":[0.9977255,0.00001343878,0.000206328,0.00001337095,0.0005220766,0.00006132323,0.0003042707,0.0000368393,0.001116832],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01361791,"threshold_uncertainty_score":0.999998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02161173919808182,"score_gpt":0.2477775767618997,"score_spread":0.2261658375638179,"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."}}