Varying Conditions for Hexanoic Acid Degradation with BioTiger™
Bibliographic record
Abstract
BioTiger™ (BT) is a consortium of 12 bacteria designed for petroleum waste biodegradation. BT is currently being studied and could be considered for bioremediation of the Athabasca oil sands refineries in Canada and elsewhere. The run-off ponds from the petroleum extraction processes, called tailings ponds, are a mixture of polycyclic aromatic hydrocarbons, naphthenic acids, hydrocarbons, toxic chemicals like heavy metals, water, and sand. Due to environmental regulations the oil industry would like to separate and degrade the hazardous chemical species from the tailings ponds while recycling the water. It has been shown that BT at 30 C° is able to completely degrade 10 mM hexanoic acid (HA) co-metabolically with 0.2% yeast extract (w/v) in 48 hours when starting at 0.4 OD 600nm. After establishing this stable degradation capability, variations were tested to explore the wider parameters of BT activity in temperature, pH, intermediate degradation, co-metabolic dependence, and transfer stability. Due to the vast differences in temperature at various points in the refineries, a wide range of temperatures were assessed. The results indicate that BT retains the ability to degrade HA, a model surrogate for tailings pond contaminants, at temperatures ranging from 15°C to 35°C. Hexanamide (HAM) was shown to be an intermediate generated during the degradation of HA in an earlier work and HAM is completely degraded after 48 hours, indicating that HAM is not the final product of HA degradation. Various replacements for yeast extract were attempted. Glucose, a carbon source; casein amino acids, a protein source; additional ammonia, mimicking known media; and additional phosphate with Wolffe’s vitamins and minerals all showed no significant degradation of HA compared to control. Decreasing the yeast extract concentration (0.05%) demonstrated limited but significant degradation. Finally, serial inoculations of BT were performed to determine the stability of degradation over several generations. Overall, BT has shown to be moderately flexible for HA co-metabolic biodegradation.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".