Perchlorate‐reducing microorganisms isolated from contaminated sites
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
An extensive microcosm survey of perchlorate-contaminated sites was undertaken to assess the ability of indigenous microorganisms to degrade perchlorate. Samples from 12 contaminated sites and from one pristine location were analysed. Perchlorate was degraded to below detection limit in all electron donor-amended microcosms. Perchlorate-reducing microorganisms (PRMs) were numerous at most of these sites. Sixteen distinct PRMs were isolated that were phylogenetically related to either Dechloromonas in the Beta Proteobacteria (9/16 isolates) or to Azospirillum in the Alpha Proteobacteria (7/16 isolates). The majority of previously isolated PRMs are in the Beta Proteobacteria related to Dechloromonas or Dechlorosoma. This study indicates that PRMs of the genus Azospirillum may be more prevalent at contaminated sites than the current record of isolates suggests. Cell yields, electron donor to perchlorate ratios and maximum specific growth rates were similar among the isolates and similar to the few previously published values. However, the Monod half-saturation constants for perchlorate for the two Azospirillum isolates characterized were lower than those measured for other genera, suggesting that they may be more effective at low concentrations of perchlorate. These results extend the current understanding of PRMs from diverse environments and provide added confidence that microbial perchlorate reduction is ubiquitous, even at highly contaminated sites, and can be harnessed effectively for bioremediation.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.028 | 0.011 |
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 it