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Record W2922000038 · doi:10.2166/wqrj.2000.024

Characterizing Stormwater Sediments for Ecotoxic Risk

2000· article· en· W2922000038 on OpenAlexaffabout
Gabriel vanLoon, Bruce C. Anderson, W. E. Watt, Jiří Maršálek

Bibliographic record

VenueWater Quality Research Journal · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsQueen's University
Fundersnot available
KeywordsStormwaterEnvironmental scienceSedimentMultidisciplinary approachDeposition (geology)ParticulatesEcosystemWater qualityContaminationWater resource managementEnvironmental engineeringEnvironmental planningEnvironmental resource managementEnvironmental protectionSurface runoffGeologyEcology

Abstract

fetched live from OpenAlex

Abstract The characteristics of accumulated sediments were investigated, with a focus on selected trace metals, in three Stormwater management facilities and one natural site, all located in the Regional Municipality of Ottawa-Carleton, in Ontario, Canada. This study was conducted in response to concerns expressed by Environment Canada about possible ecosystem impacts by contaminants accumulated in these commonly utilized, passive treatment systems. Also of interest were the effects of facility configuration and operation and maintenance on particulate deposition patterns and resulting exposure risk. This was the first phase of a multidisciplinary study to quantify the risk of ecosystem effects in these systems, and results indicate that there were some significant potential risks present. In addition, results indicate that a simple comparison with provincial sediment quality guidelines may not be sufficient to alert facility owners and operators to these potential risks.

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)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.659
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0290.007

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 head0.110
GPT teacher head0.380
Teacher spread0.270 · 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 designNot applicable
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

Citations17
Published2000
Admission routes2
Has abstractyes

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