Anaerobic Biodegradation of Vegetable Oil Spills
Bibliographic record
Abstract
ABSTRACT Vegetable oil spills are common in the United States and Canada. Although vegetable oils usually are not toxic in the classic sense, at least not to the extent normally associated with crude oil and refined petroleum products, they can cause severe harmful effects in contaminated ecosystems. Since most of the adverse environmental effects of vegetable oils appear to be a result of the presence of the oil on the water surface, on shoreline sediments, or (in emulsified form) in the water column, a prudent spill response is to remove floating and suspended oil from the contaminated water body as quickly as possible. The goal of this research is to investigate a response alternative that is based on sedimentation of floating and suspended oil followed by anaerobic biodegradation in the sediments. The authors' research demonstrates that sedimentation of floating oil by formation of oil-mineral aggregates (OMAs) is possible, and that the interaction between oil and dry clay is crucial to the successful formation of negatively buoyant floes. The rate and extent of vegetable oil biodegradation under methanogenic and iron-reducing conditions in freshwater sediments have also been investigated. Anaerobic biodegradation of vegetable oil occurred in all sediments that were examined, including sediments from a river, a lake, and a wetland. Carbon and electron balances indicate that anaerobic mineralization of the added vegetable oil was complete.
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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) | 0.001 | 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".