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Record W2267411421

Lagoon Wastewater Effluent Impacts Stream Metabolism in Red River Tributaries

2016· article· en· W2267411421 on OpenAlexfundaboutno aff
Chris T. Chesworth

Bibliographic record

VenueScholarship@Western (Western University) · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
FundersMinistry of EnvironmentUniversity of Alberta
KeywordsTributaryEffluentEnvironmental scienceWastewaterHydrology (agriculture)Water resource managementEnvironmental engineeringGeographyGeologyCartography
DOInot available

Abstract

fetched live from OpenAlex

Lagoons are the most common form of sewage treatment for rural Canadian communities and may therefore be a major source of pollution to local waterways. However, the environmental effects of pulse releases of lagoon effluent are largely unknown. This study reports on changes in physicochemical conditions and stream metabolism occurring as result of summer lagoon effluent releases into Red River tributaries, Manitoba, Canada. We calculated metrics of stream metabolism using the single-station, open water method. We found that an effluent release results in a significant short-term increase in physicochemical (i.e., water nutrients, stream discharge) conditions which had a subsidy effect on stream metabolism. We also found that stream metabolism was significantly greater in effluent exposed versus unexposed reaches; however, our results suggest the degree of effect depends on whether the release occurred early or late in the summer. The findings of this study have implications for lagoon management and future stream monitoring projects aimed at evaluating the effects of lagoon wastewater effluent.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.067
GPT teacher head0.300
Teacher spread0.233 · 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 teacher head, not a consensus.

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

Citations2
Published2016
Admission routes2
Has abstractyes

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