Native freshwater lake microbial community response to an <i>in situ</i> experimental dilbit spill
Bibliographic record
Abstract
With the increase in crude oil transport throughout Canada, the potential for spills into freshwater ecosystems has increased and additional research is needed in these sensitive environments. Large enclosures erected in a lake were used as mesocosms for this controlled experimental dilbit (diluted bitumen) spill under ambient environmental conditions. The microbial response to dilbit, the efficacy of standard remediation protocols on different shoreline types commonly found in Canadian freshwater lakes, including a testing of a shoreline washing agent were all evaluated. We found that the native microbial community did not undergo any significant shifts in composition after exposure to dilbit or the ensuing remediation treatments. Regardless of the treatment, sample type (soil, sediment, or water), or type of associated shoreline, the community remained relatively consistent over a 3-month monitoring period. Following this, metagenomic analysis of polycyclic aromatic and alkane hydrocarbon degradation mechanisms also showed that while many key genes identified in PAH and alkane biodegradation were present, their abundance did not change significantly over the course of the experiment. These results showed that the native microbial community present in a pristine freshwater lake has the prerequisite mechanisms for hydrocarbon degradation in place, and combined with standard remediation practices in use in Canada, has the genetic potential and resilience to potentially undertake bioremediation.
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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 | 0.001 | 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".