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Record W2045112420 · doi:10.2166/wst.2006.326

Impacts on water quality in the upper Elbow River

2006· article· en· W2045112420 on OpenAlexaffabout
Al Sosiak, J F Dixon

Bibliographic record

VenueWater Science & Technology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsAlberta Environment and Protected Areas
Fundersnot available
KeywordsTributaryHydrology (agriculture)Environmental scienceSurface runoffGroundwaterNitrateWater qualityTotal suspended solidsSuspended solidsFecal coliformNutrientTotal dissolved solidsPhosphorusEnvironmental engineeringWastewaterEcologyGeographyChemical oxygen demandGeologyBiology

Abstract

fetched live from OpenAlex

Recent work has found evidence of deterioration in water quality in the Elbow River upstream from Calgary, Alberta, Canada. We sampled this basin to describe spatial and temporal trends and factors that could be contributing to this deterioration. Sources near Calgary generally contributed most of the total phosphorus (TP) entering the river, and most total suspended solids (TSS) during low to average flows. During high flows, a large influx of TSS occurred further upstream. Sources of TP could include runoff from residential developments and agriculture, and groundwater, while re-suspension of bed material, erosion, and storm sewers may contribute TSS. Increasing trends in dissolved phosphorus (TDP) and ammonia suggest that sources in this reach are also contributing dissolved nutrients. Appreciable loading of nitrate + nitrite also occurred near Calgary, with a significant increasing trend in nitrate + nitrite occurring at every Elbow River site and several tributaries. Fecal coliforms have increased significantly over time at a downstream site. Runoff from residential developments, agriculture, or contributions from groundwater could account for this trend. In the 2003 bacterial source tracking study, DNA markers from ruminant animals were found in samples from most locations sampled in this basin, even at some headwaters sites, but no human markers were found.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.207

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0020.000
Open science0.0010.001
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 head0.008
GPT teacher head0.234
Teacher spread0.226 · 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 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

Citations15
Published2006
Admission routes2
Has abstractyes

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