Characterization of the bacterial community structure of Sydney Tar Ponds sediment
Bibliographic record
Abstract
The Sydney Tar Ponds is one of the largest toxic waste sites in Canada. The bacterial diversity and abundance in the Sydney Tar Ponds sediment was examined using a 16S rRNA gene clone library and denaturing gradient gel electrophoresis (DGGE) with four different primer sets. The clone library was grouped into 19 phylotypes that could be divided into five phyla: Proteobacteria (56.9%), Actinobacteria (35%), Acidobacteria (4.9%), Firmicutes (2.4%), and Verrucomicrobia (0.8%). Members of the phyla Actinobacteria (represented mainly by Mycobacterium spp.) and Alphaproteobacteria (represented by Acidocella spp.) comprised the majority of the clone library. This study also revealed that the phylogenetic results obtained from clone library analysis and from DGGE analysis, with all the primer sets, showed some variability. However, similar Mycobacterium spp. and Acidocella spp. were found in all the different DGGE analyses, again suggesting that these two genera are dominant in the Sydney Tar Ponds sediment. In addition, DGGE analysis indicated that primer sets targeting the V3 region produced results that were the most similar to those obtained with the clone library.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".