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Record W2548317763 · doi:10.1080/02626667.2016.1255747

Trend analysis of nutrient loadings in a large prairie catchment

2016· article· en· W2548317763 on OpenAlex
L. A. Morales-Marín, Kwok Pan Chun, H. S. Wheater, Karl-Erich Lindenschmidt

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHydrological Sciences Journal · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsGlobal Institute for Water SecurityUniversity of Saskatchewan
Fundersnot available
KeywordsNutrientEutrophicationEnvironmental scienceSurface runoffDrainage basinWater qualityHydrology (agriculture)StreamflowPhosphorusWatershedPopulationEcosystemEcologyGeographyBiologyGeology

Abstract

fetched live from OpenAlex

Nutrient loadings in many river catchments continue to increase due to rapid expansion of agriculture, urban and industrial development, and population growth. Nutrient enrichment of water bodies has intensified eutrophication which degrades water quality and ecosystem health. In this study, we carried out a trend analysis of total phosphorus and total nitrogen loads in the South Saskatchewan River (SSR) catchment using a novel approach to analyse nutrient time series. Seasonal analysis of trends at each of the water quality stations was performed to determine the relationships between annual flow regimes and nutrient loads in the catchment, in particular, the influence of the high spring runoff on nutrient export. Decadal analysis was also performed to determine the long-term relationships of nutrients with anthropogenic changes in the catchment. Although it was found that seasonal and historical variability of nutrient load trends is mainly determined by streamflow regime changes, there is evidence that increases in nitrogen concentration can also be attributed to anthropogenic changes.

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.

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)0.001
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 score0.034
Threshold uncertainty score0.886

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.251
Teacher spread0.236 · 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