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Implications of Aerated Stabilization Basin Dredging on Potential Effluent Toxicity to Fish

2010· article· en· W2292541396 on OpenAlexaff
Talat Mahmood, Tibor Kovács, Sharon Gibbons, Jean‐Claude Paradis

Bibliographic record

VenueWater Environment Research · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsResolute Forest Products (Canada)FPInnovations
Fundersnot available
KeywordsDredgingEffluentEnvironmental scienceAerationRainbow troutToxicityAerated lagoonEnvironmental engineeringFish <Actinopterygii>SlurryWaste managementFisheryToxicologyEnvironmental chemistryPulp and paper industrySewage treatmentEcologyChemistryBiologyEngineeringActivated sludge

Abstract

fetched live from OpenAlex

Benthal solids accumulated in aerated stabilization basins (ASBs) must be dredged to regain treatment capacity. While dredging restores treatment performance, it has been associated occasionally with the failure to meet regulatory effluent toxicity limits at the time of dredging. A first study of its kind was undertaken to investigate the implications of ASB dredging on potential effluent toxicity to fish. The study showed that benthal solid slurry removed from the quiescent zone of an ASB with a hydraulic dredge was toxic to rainbow trout with a 96-hour median lethal concentration (LC50) of 2.2%. The high ammonia concentration in the sample was the main cause of fish mortality. Hydrogen sulfide and resin and fatty acids also were present in the dredged material at concentrations that could cause fish mortality. These findings have led to best management practices that can be used to mitigate or eliminate fish toxicity issues during dredging operations.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.650
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 communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.001

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 head0.022
GPT teacher head0.284
Teacher spread0.263 · 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 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

Citations1
Published2010
Admission routes1
Has abstractyes

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