Endophytic root bacteria associated with the natural vegetation growing at the hydrocarbon-contaminated Bitumount Provincial Historic site
Bibliographic record
Abstract
, plants have been able to recolonize the site through means of natural revegetation. This study was designed to achieve a better understanding of the plant-root-associated bacterial partnerships occurring within naturally revegetated hydrocarbon-contaminated soils. Root endophytic bacterial communities were characterized from representative plant species throughout the site by both high-throughput sequencing and culturing techniques. Population abundance of rhizosphere and root endosphere bacteria was significantly influenced (p < 0.05) by plant species and sampling location. In general, members of the Actinomycetales, Rhizobiales, Pseudomonadales, Burkholderiales, and Sphingomonadales orders were the most commonly identified orders. Community structure of root-associated bacteria was influenced by both plant species and sampling location. Quantitative real-time polymerase chain reaction was used to determine the potential functional diversity of the root endophytic bacteria. The gene copy numbers of 16S rRNA and 2 hydrocarbon-degrading genes (CYP153 and alkB) were significantly affected (p < 0.05) by the interaction of plant species and sampling location. Our findings suggest that some of the bacterial communities detected are known to exhibit plant growth promotion characteristics.
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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 | 0.001 | 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) | 0.001 | 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".