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Record W2071167393 · doi:10.2134/jeq2003.5830

Relationship between Water Repellency and Native and Petroleum‐Derived Organic Carbon in Soils

2003· article· en· W2071167393 on OpenAlexafffund
Julie Roy, W. B. McGill, Heather A. Lowen, Richard L. Johnson

Bibliographic record

VenueJournal of Environmental Quality · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversity of Northern British ColumbiaImperial Oil (Canada)
FundersImperial Oil Resources
KeywordsSoil waterEnvironmental scienceTotal organic carbonPetroleumEnvironmental chemistrySoil carbonCarbon fibersSoil scienceChemistryMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

Some soils develop severe and persistent water repellency following contamination with crude oil. This study was conducted to characterize and compare the spatial distribution of soil water repellency and residual oil contamination at 12 such sites. The molarity of ethanol droplet (MED) test was used to assess soil water repellency and the content of dichloromethane-extractable organics (DEO) was used to quantify residual oil in soil. We found a relatively strong positive correlation between MED and DEO in soil (r2 = 0.74). Both variables tended to decrease abruptly with depth at 11 of the 12 study sites. Dichloromethane-extractable organics similarly decreased with depth in control adjacent soil (MED = 0 M), but from an average concentration one to two orders of magnitude lower than in water-repellent soil. Using data from corresponding control adjacent and water-repellent soils, we determined that approximately 29 and 10% of measured total organic carbon in water-repellent A- and B-horizon soil, respectively, consists of dichloromethane-insoluble organic carbon of petroleum origin. We propose that this fraction contains most of the causative agents of soil water repellency at the studied sites.

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 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)0.002
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 score0.481

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0000.000

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 head0.017
GPT teacher head0.243
Teacher spread0.226 · 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 teacher head, 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

Citations34
Published2003
Admission routes2
Has abstractyes

Explore more

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