Evaluation of Bacterial Community Structure and Its Influence on Sulfide Oxidation in a Bio-Leaching Environment
Bibliographic record
Abstract
The mechanism of sulfide oxidation by adhering bacteria (direct oxidation mechanism) and by ferric ion in the aqueous phase was studied by quantitative assessment of bacterial activity on the sulfide surface. To probe for the principal bacterial species on the surface and in the supernatant, a library of DNA genes encoding portions of bacterial 16S rRNA was constructed. The PCR-amplified DNA from the bacterial populations was cloned employing PROMEGA's pGEM-T Easy Vector system. The clone frequency indicated that iron-oxidizing bacteria were dominant in the liquid phase, while Acidithiobacillus ferroixdans, which is both sulfur and iron oxidizer was the most prevalent on the sulfide surface. Samples of crystalline pyrite were exposed to the bacterial consortium to evaluate surface alterations caused by bacteria. Chemical (abiotic) oxidation experiments with ferric ion as the oxidant were carried out in parallel with the biological oxidation tests. Changes in the surface topography were monitored by atomic force microscopy (AFM) while changes in surface chemistry were examined by Raman spectroscopy. Bacterial attachment resulted in a 53% increase in the specific surface area in comparison to a 13% increase caused by chemical (ferric ion) oxidation. The oxidation rate was assessed by evaluating the iron release. After corrections for surface area changes, the specific abiotic (oxidation by Fe3 +) and biotic oxidation rates with adhering bacteria were nearly the same (2.6 × 10− 9 mol O2/s/m2 versus 3.3 × 10− 9 mol O2/s/m2) at pH = 2 and a temperature of 25°C. The equality of rates implies that the availability of ferric ion as the oxidant is rate limiting.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".