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Record W2496203408 · doi:10.2166/wqrj.2007.027

Environmental and Economic Evaluation of Cow-Calf Wintering Site Runoff Control as a Beneficial Management Practice to Improve Surface Water Quality

2007· article· en· W2496203408 on OpenAlexafffundabout
James J. Wuite, D. S. Chanasyk, Muhammad Akbar

Bibliographic record

VenueWater Quality Research Journal · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsUniversity of AlbertaAgriculture Food and Rural Development
FundersUniversity of Alberta
KeywordsSurface runoffKjeldahl methodWater qualityEnvironmental scienceWatershedHydrology (agriculture)Nonpoint source pollutionNitrateTotal suspended solidsNitrogenSurface waterEnvironmental engineeringEcologyChemical oxygen demandChemistryEngineering

Abstract

fetched live from OpenAlex

Abstract A runoff diversion-collection system was evaluated as a beneficial management practice (BMP) for minimizing the impact of wintering site runoff on the water quality of an adjacent reach in the headwaters sub-basin of the Haynes Creek Watershed in central Alberta. Significant (α = 0.05) post-BMP mean annual load reductions of 13, 47, and 17% for dissolved, particulate, and total phosphorus, respectively, were realized. Mean annual loads of nitrate nitrogen and total Kjeldahl nitrogen were also reduced by 83 and 22%, respectively. The sum of total loads of Kjeldahl nitrogen and nitrate-plus-nitrite nitrogen, a surrogate measure of total nitrogen, also showed a reduction of 29%. However, mean annual load of total residue increased by 15%. Despite significance at the wintering site, these water quality changes were not statistically detected at the outlet of the subbasin. In spite of the measureable improvement in downstream water quality, adoption of the studied BMP represented a net economic cost to the producer under the current management conditions at the site. Furthermore, there appeared a need for concurrent implementation of BMPs in the headwaters sub-basin to be able to register any detectable changes in water quality at its outlet.

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)0.035
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.349
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0350.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.050
GPT teacher head0.388
Teacher spread0.338 · 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
Published2007
Admission routes3
Has abstractyes

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