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Record W7014730325

Remediation of brine-contaminated soil using calcium nitrate, gypsum, and straw

2013· dissertation· en· W7014730325 on OpenAlexaffabout

Bibliographic record

VenueMspace (University of Manitoba) · 2013
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsUniversity of WinnipegUniversity of Manitoba
Fundersnot available
KeywordsEnvironmental remediationGypsumStrawLeaching (pedology)LimeSoil waterCalcium nitrateCalciumPermanent wilting point
DOInot available

Abstract

fetched live from OpenAlex

Salt-affected soils from point source brine contamination are common in the active oil field in SE Saskatchewan. A remediation process that included dewatering by sub-surface tile drains, application of surface amendments (calcium nitrate and straw), and growing forages has been successful but not previously examined. In a field study of two remediation sites, the changes in vegetation, soil salinity, and groundwater were assessed using geo-referenced electromagnetic (EM) maps (EM38h, EM38v, and EM31v), piezometers, and soil sampling. A laboratory soil core leaching experiment studied the effect of gypsum, calcium nitrate, and straw at various rates on the remediation of a brine-contaminated soil. All treatments including the control reduced the electrical conductivity (EC) to non-saline values (<4 dS m-1). The sodium adsorption ratio (SAR) was reduced to <13 with the high rates of gypsum and calcium nitrate. The fastest and most effective treatments were comprised of all rates of gypsum and the highest rate of calcium nitrate.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.020
GPT teacher head0.214
Teacher spread0.194 · 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 designBench or experimental
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
Published2013
Admission routes2
Has abstractyes

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