MétaCan
Menu
Back to cohort
Record W2160284634 · doi:10.1897/02-627

Distribution of acidic and neutral drugs in surface waters near sewage treatment plants in the lower Great Lakes, Canada

2003· article· en· W2160284634 on OpenAlexaffabout
Chris D. Metcalfe, Xiu‐Sheng Miao, Brenda G. Koenig, John Struger

Bibliographic record

VenueEnvironmental Toxicology and Chemistry · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsEnvironment and Climate Change CanadaTrent University
Fundersnot available
KeywordsSurface waterEffluentEnvironmental scienceSewage treatmentSewageWater pollutionHydrology (agriculture)STREAMSEnvironmental chemistryEnvironmental engineeringChemistryGeology

Abstract

fetched live from OpenAlex

Prescription and nonprescription drugs have been detected in rivers and streams in Europe and the United States. Sewage treatment plants (STPs) are an important source of these contaminants, but few data exist on the spatial distribution of drugs in surface waters near STPs. Samples of surface water were collected in the summer and fall of 2000 at open-water sites in the lower Great Lakes (Lake Ontario and Lake Erie), at sites near the two STPs for the city of Windsor (ON, Canada), and at sites in Hamilton Harbour (ON, Canada), an embayment of western Lake Ontario that receives discharges from several STPs. In a follow-up study in the summer of 2002, samples of surface water and final effluent from adjacent STPs were collected from sites in Hamilton Harbour and Windsor. In addition, surface water and STP effluent samples were collected in Peterborough (ON, Canada). All samples of surface water and STP effluents were analyzed for selected acidic and neutral drugs. In the survey of Hamilton Harbour and Windsor conducted in 2000, acidic drugs and the antiepileptic drug carbamazepine were detected at ng/L concentrations at sites that were up to 500 m away from the STP, but the hydrological conditions of the receiving waters strongly influenced the spatial distribution of these compounds. Drugs were not detected at open-water locations in western Lake Erie or in the Niagara River near the municipality of Niagara-on-the-Lake (ON, Canada). However, clofibric acid, ketoprofen, fenoprofen, and carbamazepine were detected in samples collected in the summer of 2000 at sites in Lake Ontario and at a site in the Niagara River (Fort Erie, ON, Canada) that were relatively remote from STP discharges. Follow-up studies in the summer of 2002 indicated that concentrations of acidic and neutral drugs in surface waters near the point of sewage discharge into the Little River (ON, Canada) STP were approximately equal to the concentrations in the final effluent from the STP. Caffeine and cotinine, a metabolite of nicotine, were generally present in STP effluents and surface waters contaminated by drugs. The antidepressant fluoxetine and the antibiotic trimethoprom were also detected in most STP effluents and some surface water samples. For the first time, the lipid regulating drug atorvastatin was detected in samples of STP effluent and surface water.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.211
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations629
Published2003
Admission routes2
Has abstractyes

Explore more

Same venueEnvironmental Toxicology and ChemistrySame topicPharmaceutical and Antibiotic Environmental ImpactsFrench-language works237,207