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Record W2895842954 · doi:10.1080/15320383.2018.1513990

NAPL mobility of OPA-containing sediments

2018· article· en· W2895842954 on OpenAlexaff
Jeffrey A. Johnson, Deborah A. Edwards, Douglas Blue, Sara J. Morey

Bibliographic record

VenueSoil and Sediment Contamination An International Journal · 2018
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsImperial Oil (Canada)
Fundersnot available
KeywordsParticle (ecology)Phase (matter)Capillary actionAqueous two-phase systemSedimentCentrifugeMineralogyChemical engineeringChemistryGeologyMaterials scienceComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

In situ deposited non-aqueous phase liquid (IDN) sediments have unique characteristics that inherently mitigate the movement of separate phase liquids. IDN sediments are composed of oil-particle aggregates (OPAs). OPAs consist of an oil bead or globule with attached solid particles, such as clay platelets, silt and sand granules, and/or organic materials. IDN sediments develop at locations where a continual or near continual discharge of non-aqueous phase liquids (NAPLs) have occurred over a period of time. IDN sediments consist of an open network of small pores where fluids are retained. Although the pore structure is very open, the pore openings are relatively small, which appears to inhibit fluid movement. In particular, capillary pressure analyses indicate that NAPL was not generally released until pressures of at least 15 pounds per square inch (psi) were induced. In addition, centrifuge testing at 1,000 G shows that NAPL immobility is observed in samples at NAPL saturations as high a 12%. These data suggest that NAPL is retained within the smallest pores and is encapsulated within a network of larger pores filled with water. Although the sediment contains NAPL, this original OPA structure appears to inhibit the oil beads from coalescing, preventing NAPL flow.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.805
Threshold uncertainty score0.435

Codex and Gemma teacher scores by category

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 communication0.0000.001
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 head0.010
GPT teacher head0.270
Teacher spread0.260 · 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 designOther design
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

Citations5
Published2018
Admission routes1
Has abstractyes

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