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Record W2090448769 · doi:10.1080/713609921

An Ecological Risk Assessment of Ammonia in the Aquatic Environment

2003· article· en· W2090448769 on OpenAlexaffabout
Miles Constable, Murray N. Charlton, F. C. Jensen, Karen McDonald, Gordon Craig, Ken Taylor

Bibliographic record

VenueHuman and Ecological Risk Assessment An International Journal · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsGolder Associates (Canada)Environment and Climate Change CanadaAlberta Environment and Protected Areas
Fundersnot available
KeywordsEnvironmental scienceWastewaterAquatic ecosystemEffluentEcosystemAquatic environmentSewage treatmentRisk assessmentEnvironmental engineeringEcologyRisk analysis (engineering)Environmental protectionBusinessBiologyComputer science

Abstract

fetched live from OpenAlex

Ammonia is released in the environment by many industries and other human activities. The major quantifiable sources of ammonia released to aquatic ecosystems across Canada are municipal wastewater treatment plants, at an estimated total quantity of 62,000 tonnes per year. Given the sources of ammonia releases in the environment and the properties of the substance, terrestrial plants and aquatic organisms are potential risk targets. A tiered assessment approach has been used to determine the ecological risk in the aquatic environment from ammonia released in municipal wastewater effluents. The results obtained for two case studies with the probabilistic risk analysis used in the highest tier support the conclusion that the conditions encountered in these two locations can lead to ammonia concentrations capable of producing an adverse ecological impact.

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.033
GPT teacher head0.352
Teacher spread0.319 · 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 designSimulation or modeling
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

Citations132
Published2003
Admission routes2
Has abstractyes

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