Biodegradation of Diesel Fuel in Soil Under Various Nitrogen Addition Regimes
Bibliographic record
Abstract
Bioremediation is a growing technology for treating fuel-contaminated soils. Many biological, physical, and chemical parameters control the rate and efficiency of this process, including type and concentration of contaminants, temperature, oxygen content, and nutrient status. This study investigated the effect that nitrogen sources and concentrations had on the degradation rate of diesel fuel in nutrient limited soil at two carbon-to-nitrogen ratios. The different sources of nitrogen studied were ammonium nitrate, ammonium sulfate, potassium nitrate, urea, and urea oligomers (control release fertilizer). Laboratory experiments were conducted on field-contaminated soil using sealed bioreactors at a controlled temperature of 25°C. For both carbon-to-nitrogen ratios tested, hydrocarbon degradation rates were the highest for the ammonium sulfate (20:1 at 0.032 d−1; 40:1 at 0.019d−1) and urea treatments (20:1 at 0.025 d−1; 40:1 at0.011 d−1). A degradation rate correlation as a function of nitrate and ammonia concentrations was developed. The correlation suggests the occurrence of nitrate inhibition at elevated nitrate concentrations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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".