Polyphasic microbial community analysis of petroleum hydrocarbon-contaminated soils from two northern Canadian communities
Bibliographic record
Abstract
The cold-adapted bacterial communities in petroleum hydrocarbon-contaminated and non-impacted soils from two northern Canadian environments, Kuujjuaq, Que., and Alert, Nunavut, were analyzed using a polyphasic approach. Denaturing gradient gel electrophoresis (DGGE) separation of 16S rDNA PCR fragments from soil total community DNA revealed a high level of bacterial diversity, as estimated by the total number of bands visualized. Dendrogram analysis clustered the sample sites on the basis of geographical location. Comparison of the overall microbial molecular diversity suggested that in the Kuujjuaq sites, contamination negatively impacted diversity whereas in the Alert samples, diversity was maintained or increased as compared to uncontaminated controls. Extraction and sequencing analysis of selected 16S rDNA bands demonstrated a range of similarity of 86-100% to reference organisms, with 63.6% of the bands representing high G+C Gram-positive organisms in the order Actinomycetales and 36.4% in the class Proteobacteria. Community level physiological profiles generated using Biolog GN plates were analyzed by cluster analysis. Based on substrate oxidation rates, the samples clustered into groups similar to those of the DGGE dendrograms, i.e. separation based upon geographic origin. The coinciding results reached using culture-independent and -dependent analyses reinforces the conclusion that geographical origin of the samples, rather than petroleum contamination level, was more important in determining species diversity within these cold-adapted bacterial communities.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".