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Record W2034718886 · doi:10.1897/05-571r.1

Seasonality effects on pharmaceuticals and <i>s</i>-triazine herbicides in wastewater effluent and surface water from the Canadian side of the upper Detroit River

2006· article· en· W2034718886 on OpenAlexaffabout
Wen Yi Hua, Erin R. Bennett, Xui‐Sheng Maio, Chris D. Metcalfe, Robert J. Letcher

Bibliographic record

VenueEnvironmental Toxicology and Chemistry · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsCarleton UniversityTrent UniversityUniversity of Windsor
Fundersnot available
KeywordsAtrazineEffluentSimazineEnvironmental chemistrySurface waterWastewaterSewage treatmentEnvironmental scienceSewageChemistryPesticideEnvironmental engineeringBiologyEcology

Abstract

fetched live from OpenAlex

The influence of seasonal changes in water conditions and parameters on several major pharmacologically active compounds (PhACs) and s-triazine herbicides was assessed in the wastewater and sewage treatment plant (WSTP) effluent as well as the downstream surface water from sites on the Canadian side of the upper Detroit River, between the Little River WSTP and near the water intake of a major drinking water treatment facility for the City of Windsor (ON, Canada). The assessed PhACs were of neutral (carbamazepine, cotinine, caffeine, cyclophosphamide, fluoxetine, norfluoxetine, pentoxifylline, and trimethoprim) and acidic (ibuprofen, bezafibrate, clofibric acid, diclofenac, fenoprofen, gemfibrozil, indomethacin, naproxen, and ketoprofen) varieties. The major assessed s-triazine herbicides were atrazine, simazine, propazine, prometon, ametryn, prometryn, and terbutryn. At sampling times from September 2002 to June 2003, 15 PhACs were detected in the WSTP effluent at concentrations ranging from 1.7 to 1244 ng/L. The PhAC concentrations decreased by as much 92 to 100% at the Little River/Detroit River confluence because of the river dilution effect, with further continual decreases at sites downstream from the WSTP. The only quantifiable s-triazine in WSTP effluent, atrazine, ranged from 6.7 to 200 ng/L and was higher in Detroit River surface waters than in WSTP effluent. Only carbamazepine, cotinine, and atrazine were detectable at the low-nanogram and subnanogram levels in surface waters near a drinking water intake site. Unlike the PhACs, atrazine in the Detroit River is not attributable to point sources, and it is heavily influenced by seasonal agricultural usage and runoff. Detroit River surface water concentrations of carbamazepine, cotinine, and atrazine may present a health concern to aquatic wildlife and to humans via the consumption of drinking 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)0.000
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 score0.318
Threshold uncertainty score0.640

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.007
GPT teacher head0.222
Teacher spread0.214 · 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

Citations85
Published2006
Admission routes2
Has abstractyes

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