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Record W2512972894 · doi:10.1680/jenge.15.00035

Degradation and mobility of petroleum hydrocarbons in oil sand waste

2016· article· en· W2512972894 on OpenAlexaffabout
Kyle O Scale, Tomasz Korbas, Ian R Fleming

Bibliographic record

VenueEnvironmental Geotechnics · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsLand reclamationOverburdenEnvironmental sciencePetroleumOil sandsGroundwaterSoil waterCarbon dioxideHydrocarbonBiodegradationWaste managementFossil fuelEnvironmental engineeringMining engineeringGeologyEnvironmental chemistryGeotechnical engineeringSoil scienceAsphaltChemistryArchaeology

Abstract

fetched live from OpenAlex

In Northern Alberta, Canada, large volumes of low-grade ‘lean’ oil sand (LOS) overburden are translocated during the surface mining of oil sands and remain in future reclaimed landscapes. The objectives addressed in this paper are to (a) characterise the on-site petroleum hydrocarbon (PHC) content of LOS; (b) evaluate the effect of LOS temperature on rates of carbon dioxide (CO2) flux and PHC biodegradation and (c) evaluate the potential for PHC to leach from LOS into groundwater. The results show that LOS is predominantly composed of heavier F3 and F4 PHC fractions, the temperature appears to affect carbon dioxide fluxes and PHC degradation rates and it is unlikely that the presence of LOS in reclamation soils will release significant quantities of PHC into groundwater.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.515
Threshold uncertainty score0.976

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 communication0.0010.000
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 head0.005
GPT teacher head0.178
Teacher spread0.173 · 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 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

Citations4
Published2016
Admission routes2
Has abstractyes

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