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Record W2071833472 · doi:10.4141/cjss07037

Variability of vertical bromide redistribution within hummocky landscape

2008· article· en· W2071833472 on OpenAlexafffundvenueabout
J. Thibodeau, D. S. Chanasyk, L. G. Fuller

Bibliographic record

VenueCanadian Journal of Soil Science · 2008
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsNational Research Council CanadaAlberta Environment and Protected AreasUniversity of AlbertaBiotechnology Research Institute
FundersUniversity of AlbertaAlliance for Accelerating Excellence in Science in AfricaAlberta Agricultural Research InstituteAlberta Crop Industry Development Fund
KeywordsLeaching (pedology)SnowmeltEnvironmental scienceBromideGroundwaterHydrology (agriculture)Soil scienceSoil waterChemistryGeologySnowGeomorphologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Groundwater quality is a major issue for rural communities, and intensive agricultural practices have the potential to contaminate groundwater via leaching. By analysing the movement of a bromide tracer over three slope positions (top, middle and low) within two hummocky landscapes in central Alberta, the intensity of short-term leaching potential was measured, and the accuracy of a leaching potential index was assessed. Concentrations of bromide > 1 mg kg-1 were found at a 120-cm depth at each slope position, from both landscapes, after one snowmelt event and one growing season. However, the depth of a bromide concentration > 100 mg kg-1 varied significantly among slope positions after the snowmelt event, and after the growing season. The leaching potential index successfully distinguished between high leaching potential, and low and very low leaching potential. This index will become a useful tool to determine the variability of leaching within an agricultural landscape. Key words: Soil-landscape, leaching, tracer, soil moisture, soil profile index

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 score0.316
Threshold uncertainty score0.629

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.010
GPT teacher head0.192
Teacher spread0.182 · 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

Citations6
Published2008
Admission routes4
Has abstractyes

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