Effect of Biodiesel Addition on Microbial Population in Diesel Storage Tanks
Bibliographic record
Abstract
Abstract Microbial activity is a concern in the fuel industry. The water layer developed at the bottom of storage tanks constitutes an environment with the necessary conditions for development of microorganisms that can interact and affect the infrastructure in fuel facilities. The use of biodiesel as an alternative to fossil fuels leads to the question if the microbial communities established in fuel facilities are going to stay stable or if they are going to change due to the presence of this new compound. Being aware of these changes is important because changes in microorganisms community can lead to the development of a population in which the species present are more susceptible to interact and corrode the infrastructure. In the present work we explore how the addition of biodiesel can affect microbial interactions with polyethylene by using a model microbial community obtained from a diesel storage tank. Blends of 0, 25, 50, 75 and 100% biodiesel are evaluated during 50 days. The interaction of microbial populations with polyethylene is studied through biofilm quantification and SEM imaging of plastic surfaces. The heterothrophic composition of the population is studied through culture in differential media for fungi, bacteria and anaerobes.
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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".