A simple procedure for elimination of fungal contamination for enumeration of iron-oxidizing bacteria from bioleaching matrix of sewage sludge
Bibliographic record
Abstract
Enumeration of iron-oxidizing bacteria from the bioleaching matrix of sewage sludge is always confronted by fungal contamination. The objective of the present study was to find a reliable and simple method to remove fungal growth and to shorten the incubation time for facilitating enumeration of the iron-oxidizers from complex sludge samples. The results demonstrated that filtering the sludge sample through sterile No. 5 Whatman filter paper before serial dilution was effective in eliminating the fungal growth on agarose media. Both the counts and the incubation time required for enumeration were highly dependent on the medium pH, with maximum counts at pH 2.5-2.75. Medium prepared at pH values outside of this range led to lower counts and a longer lag time for colony formation. However, the introduction of heterotrophic microorganisms into the solid medium did not show further improvement in enumeration efficiency and shortening of the incubation period. By incorporating the optimal conditions obtained, the incubation time could be reduced to 7 and 10 d for pure cultures and sludge samples, respectively.
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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 | 0.000 | 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) | 0.000 | 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".