Microbial distribution and diversity in saturated, high pH, uranium mine tailings, Saskatchewan, Canada
Bibliographic record
Abstract
Microbiological analyses were conducted on core samples collected along a vertical profile (0-66 m below surface) from the tailings management facility (TMF) at the Rabbit Lake uranium mine in northern Saskatchewan, Canada. Bacterial numbers in the core materials were similar to surrounding soils and surface waters, regardless of the seemingly unfavorable pH (mean=9.9) and temperature (approximately 0 degrees C) in the TMF. The greatest number of viable cells (105 CFU/g) was detected at the interface between the tailings and overlying standing water, below which cell counts decreased rapidly with depth. Whole-community metabolic profiles for samples from the different depths grouped into 3 clusters; however, these groups could not be positively correlated with sampling depth, temperature, redox potential, pH, or ore-mill feed. Flow-cell studies demonstrated microbial communities in the tailings surface water could develop biofilms and maintain cell activity at both pH 10 and 7, and altering the pH between these 2 values had little effect on biofilm viability. These results demonstrate the resilience and adaptive nature of naturally occurring microbial communities and signify a potential role of microbial activity in the long-term geochemical evolution of the TMF.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| 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".