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Occurrence of Pharmaceuticals in Calgary's Wastewater and Related Surface Water

2015· article· en· W2415680866 on OpenAlexaboutno aff
Menglin Chen, Victoria I. Cooper, Jiaqi Deng, Prasanna L. Amatya, Dalibor Ambrus, Shuangshi Dong, Nancy Stalker, Catalina Nadeau-Bonilla, Janki K. Patel

Bibliographic record

VenueWater Environment Research · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsWastewaterSurface waterEnvironmental scienceEnvironmental engineering

Abstract

fetched live from OpenAlex

The influents/effluents from Calgary's water resource recovery facilities and the surface water were analyzed for pharmaceuticals in the present study. The median concentrations in the effluents for the 15 targeted pharmaceuticals were within the range of 0.006 to 3.32 ppb. Although the wastewater treatment facilities were not designed to remove pharmaceuticals, this study indicates that the wastewater treatment processes are effective in removing some of the pharmaceuticals from the aqueous phase. The removal rate estimated can be 99.5% for caffeine, whereas little or no removal was observed for carbamazepine. Biodegradation, chemical degradation, and sorption could be some of the mechanisms responsible for the removal of pharmaceuticals. The drug residues in downstream surface water could be associated with incomplete removal of pharmaceuticals during the treatment process and may lead to concerns in terms of potential impacts on the aquatic ecosystem. However, this study does not indicate any immediate risks to the downstream aquatic environment.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.100
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.004

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 head0.106
GPT teacher head0.365
Teacher spread0.259 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
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

Citations20
Published2015
Admission routes1
Has abstractyes

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