Effects of Low Temperature and Freeze-Thaw Cycles on Hydrocarbon Biodegradation in Arctic Tundra Soil
Bibliographic record
Abstract
Degradation of petroleum hydrocarbons was monitored in microcosms with diesel fuel-contaminated Arctic tundra soil incubated for 48 days at low temperatures (-5, 0, and 7 degrees C). An additional treatment was incubation for alternating 24-h periods at 7 and -5 degrees C. Hydrocarbons were biodegraded at or above 0 degrees C, and freeze-thaw cycles may have actually stimulated hydrocarbon biodegradation. Total petroleum hydrocarbon (TPH) removal over 48 days in the 7, 0, and 7 and -5 degrees C treatments, respectively, was 450, 300, and 600 microg/g of soil. No TPH removal was observed at -5 degrees C. Total carbon dioxide production suggested that TPH removal was due to biological mineralization. Bacterial metabolic activity, indicated by RNA/DNA ratios, was higher in the middle of the experiment (day 21) than at the start, in agreement with measured hydrocarbon removal and carbon dioxide production activities. The total numbers of culturable heterotrophs and of hydrocarbon degraders did not change significantly over the 48 days of incubation in any of the treatments. At the end of the experiment, bacterial community structure, evaluated by ribosomal intergenic spacer length analysis, was very similar in all of the treatments but the alternating 7 and -5 degrees C treatment.
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 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".