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Record W2308309141

Application of geophysics and numerical modelling in studying aquifer heterogeneity and nitrate transport, Abbotsford-Sumas aquifer, British Columbia, and Washington, USA

2006· dissertation· en· W2308309141 on OpenAlexaboutno aff
Sarah A. Q. McArthur

Bibliographic record

VenueSummit (Simon Fraser University) · 2006
Typedissertation
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsnot available
Fundersnot available
KeywordsAquiferHydrology (agriculture)GeologyGroundwaterEnvironmental scienceGeotechnical engineering
DOInot available

Abstract

fetched live from OpenAlex

Heterogeneity within the sand and gravel deposits of the Abbotsford-Sumas aquifer has a significant impact upon groundwater movement and nitrate transport. Using GPR and borehole logging, the scale of heterogeneity was determined, with fining upward sequences up to 5 m thick and continuous over 10’s of metres. Smaller heterogeneities were also identified visually in a local gravel pit. Various approaches were examined to represent this heterogeneity within a local groundwater flow mode l. The use of vertical anisotropy proved to be most realistic. Ages determined from the model were 60-80% lower than measured isotopic ages due to the inability to adequately represent the tortuosity of the flow paths. The spatial distribution and temporal variation of nitrate in the aquifer provided initial and calibration nitrate concentrations for the nitrate transport model. Nitrate concentrations thought to be reaching the aquifer based on recent BMPs are not sufficient to produce the observed nitrate concentrations.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.462
Threshold uncertainty score0.929

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.009
GPT teacher head0.192
Teacher spread0.183 · 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 designSimulation or modeling
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

Citations0
Published2006
Admission routes1
Has abstractyes

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