Acidophilic microbial communities associated with a natural, biodegraded hydrocarbon seepage
Bibliographic record
Abstract
Characterization of microbial communities present in a surface petroleum seep in which hydrocarbons have been biodegraded for thousands of years in order to improve the understanding on natural petroleum biodegradation. DNA was extracted from a natural, surface petroleum seep and subjected to culture independent analysis (rRNA gene-based denaturing gradient gel electrophoresis and phylogenetic analysis of clone libraries). Molecular analysis suggested dominance by acidophilic bacteria, especially Alphaproteobacteria (mainly bacteria related to Acidiphilium and Acidocella). Archaea were not detected, but fungi were present. pH of the samples was around 3.5. Acidophilic microbial communities are associated with an acidic petroleum seep. Microbial community structure analysis gives information on the environmental conditions under which petroleum biodegradation occurs. This knowledge could be applied to define conditions for specific cultivation or activity measurements. The activity of acidophilic micro-organisms deserves more attention with respect to their involvement in natural petroleum degradation. This knowledge will contribute to the design of oil bioremediation strategies for polluted acidic settings.
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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 | 0.000 | 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".