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Record W2042116897 · doi:10.4141/s06-067

Indicator of risk of water contamination by phosphorus: Temporal trends for the Province of Quebec from 1981 to 2001

2007· article· en· W2042116897 on OpenAlexaffvenueabout
Éric van Bochove, Georges Thériault, Farida Dechmi, Marie-Line Leclerc, Nadia Goussard

Bibliographic record

VenueCanadian Journal of Soil Science · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsAgricultureManureEnvironmental scienceSurface runoffPhosphorusSoil waterContaminationLivestockFertilizerRisk assessmentAgricultural landCropHydrology (agriculture)GeographyEnvironmental protectionAgronomyForestryEcologySoil scienceChemistryBiology

Abstract

fetched live from OpenAlex

An indicator of risk of water contamination by phosphorus (IROWC-P) was developed to estimate the risk of phosphorus (P) contamination in water by agriculture, and to evaluate how this risk changes over time based on the census data obtained every 5 yr. For the province of Quebec, IROWC-P is calculated with census data from 1981, 1986, 1991, 1996 and 2001. In 2001, 85% of the Soil Landscapes of Canada (SLC) agricultural polygons of Quebec were in the low and moderate risk classes and the remaining 15% in the high risk class. Although agricultural production statistics show marked changes from 1981 to 2001 in livestock herd composition, area under cultivation, agricultural land use and use of inorganic phosphorus fertilizer and animal manure, no trend was observed in the estimated risk over the same period. Increased risk of P transport from agricultural fields to water is expected when agricultural soils are rich in P or have excess P relative to crop needs and have a high potential for soil erosion and surface runoff. Key words: Risk indicator, water contamination, phosphorus, soil landscapes of Canada, agriculture

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)0.001
metaresearch head score (Gemma)0.002
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 score0.025
Threshold uncertainty score0.178

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.005
GPT teacher head0.203
Teacher spread0.198 · 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

Citations16
Published2007
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Soil ScienceSame topicSoil and Water Nutrient DynamicsFrench-language works237,207