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Record W2330185265 · doi:10.1680/jees.2013.0012

Adsorption of a jet fuel on a model organic–clay soil: Application of small angle neutron scattering

2013· article· en· W2330185265 on OpenAlexvenueno aff
H. J. M. Hanley, Timothy E. Payne

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2013
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsnot available
Fundersnot available
KeywordsAdsorptionEnvironmental remediationClay mineralsDispersion (optics)BromideOrganic matterSmall-angle neutron scatteringAqueous solutionChemistryChemical engineeringNeutron scatteringEnvironmental chemistryContaminationMineralogyInorganic chemistryNeutronOrganic chemistryNuclear physicsPhysics

Abstract

fetched live from OpenAlex

Small angle neutron scattering (SANS) data are reported from a system that models the contamination of a clay–organic matter soil from a fuel spillage. The soil was represented as an aqueous dispersion of the synthetic clay mineral Laponite coated with lysine, and the contaminant was a representative jet fuel, quadricyclane, mixed with the detergent cetyltrimethylammonium bromide (CTAB). The adsorbed surface coverage on the clay was estimated. It is shown that the presence of adsorbed lysine considerably enhances the subsequent adsorption of both CTAB and quadricyclane. It is demonstrated that the SANS technique can contribute to the general problem of environmental remediation and retention by probing the interactions of pollutants and clay surfaces.

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 score0.007
Threshold uncertainty score0.014

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)0.0000.000

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 head0.006
GPT teacher head0.176
Teacher spread0.170 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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