Use of a novel biomarker, botryococcane, to monitor biodegradation of two lacustrine‐sourced crude oils
Bibliographic record
Abstract
Abstract Bioremediation is a proven alternative for remediating petroleum‐impacted soils at exploration and production (E&P) sites. Monitoring remediation performance can involve detection and quantification of biodegradation resistant compounds such as C3017α(H),21β(H)‐hopane, which requires the use of gas chromatography with mass spectrometry detection (GC/MS). Due to the remoteness of many E&P sites, this technology is not always available, and alternative methods are needed to provide reliable quantitative measurements of petroleum remediation efficiency. This study provides a detailed chemical characterization of lacustrine‐sourced crude oils and a technical basis for measuring the effectiveness of bioremediation efforts for soil impacted by those crudes. We show that the novel isoprenoid hydrocarbon botryococcane is relatively stable in lacustrine‐sourced crude oils compared with C3017α(H),21β(H)‐hopane under moderate biodegradation conditions generally observed in field samples. We have also demonstrated that, due to the stability and relatively elevated concentration of botryococcane in lacustrine oils, it can be reliably measured using the more cost‐effective and available GC/FID methodology, and thereby be used to monitor the progress of ongoing soil bioremediation activities at remote sites.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".