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Record W3176246910 · doi:10.1016/j.watcyc.2021.06.002

Quantifying phosphorous loadings in the Thames River in Canada

2021· article· en· W3176246910 on OpenAlexaffabout
Tony Van Rossum, Yaghoub Norouzi

Bibliographic record

VenueWater Cycle · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsEnvironmental scienceHydrology (agriculture)Drainage basinWetlandEutrophicationGeologyEcologyGeotechnical engineeringGeographyNutrient

Abstract

fetched live from OpenAlex

The Canada Ontario agreement requires reduction of total phosphorous (TP) loadings to prevent algae blooms in Lake Erie. This study was to consider TP loadings from the Thames River and potential methods needed to determine actual loadings. The study found TP loading in the Thames River was dominated by peak flow events and between 10 and 15% of the flow had over 60% of the loading. Identification of TP and Dissolved Reactive Phosphate (DRG) and/or Ortho phosphorous (Ortho P) have similar ratios with TP in the Thames River although are not the same in the main, north and south branches. Continuous ortho P monitoring equipment could be used to estimate TP loads based on ratios of Ortho P to TP established in the river shed. A description and cost estimate for a continuous monitoring system is included in the study. Reduction of TP loadings requires methods that can deal with the peak flows and one option could be wetlands along the river basin.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.023
Threshold uncertainty score0.182

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.190
Teacher spread0.181 · 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.

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

Citations5
Published2021
Admission routes2
Has abstractyes

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