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Record W2156583979 · doi:10.1039/b403874f

Characterisation of weathered hydrocarbon wastes at contaminated sites by GC-simulated distillation and nitrous oxide chemical ionisation GC-MS, with implications for bioremediation

2004· article· en· W2156583979 on OpenAlexaffabout
Simon Pollard, Steve E. Hrudey, Marv Rawluk, Bryan J. Fuhr

Bibliographic record

VenueJournal of Environmental Monitoring · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsUniversity of Alberta
FundersBiotechnology and Biological Sciences Research Council
KeywordsBioremediationEnvironmental chemistryChemistryContaminationAlkylbenzenesAsphalteneHydrocarbonDistillationSoil waterSoil contaminationVacuum distillationNitrous oxideGas chromatographyEnvironmental scienceChromatographyOrganic chemistrySoil scienceBenzene

Abstract

fetched live from OpenAlex

An extended analytical characterisation of weathered hydrocarbons isolated from historically contaminated sites in Alberta is presented. The characterisation of soil extracts, chromatographically separated into component classes, by GC-simulated distillation and nitrous oxide (N2O) chemical ionisation (CI) GC-MS provides new insights into the composition of the residual oil at these sites, the principal partition medium for risk critical components. The combined polar and asphaltene content of representative soil extracts ranged from 40% w/w to 70% w/w of the oils encountered. An abundance of C14-C22 2-4 ring alicyclics, alkylbenzenes and benzocycloparaffins is prevalent within the saturate fractions of site soils. Implications for the partitioning of risk critical compounds at sites with weathered hydrocarbons and the practical application of bioremediation technologies are discussed.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.179
Threshold uncertainty score0.492

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 communication0.0000.000
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 head0.008
GPT teacher head0.207
Teacher spread0.199 · 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 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

Citations9
Published2004
Admission routes2
Has abstractyes

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