Minimal changes in microbial abundances and diversity over 7 years of emplacement for modules of compacted bentonite exposed to natural groundwater
Bibliographic record
Abstract
ABSTRACT The multi-national in situ Materials Corrosion Test (MaCoTe), being conducted at the Grimsel Test Site in Switzerland, assesses the stability of bentonite as it may be utilized within deep geological repositories (DGRs), which are proposed for the safe, long-term disposal of used nuclear fuel. This experiment provides an opportunity for long-term assessments of changes in microbial communities associated with compacted subsurface bentonite samples exposed to a natural groundwater. Leveraging samples from MaCoTe, herein, we report temporal data for the abundance and community composition of microorganisms associated with compacted bentonite samples emplaced over 7 years under in situ subsurface conditions. Phospholipid fatty acid analysis, 16S rRNA gene quantification and sequencing, cultivation, and natural organic matter analyses all indicated no significant changes for microbial community abundances associated with inner layers of bentonite samples over the 7 years. While microbial abundances did not change in the inner layers, the PLFA data suggest potential changes in microbial community composition and could also indicate prolonged microbial turnover rates. Overall, the results support microbial stability in compacted bentonite exposed to DGR-like conditions for at least 7 years. IMPORTANCE Long-term assessments of changes in microbial activity in compacted low-biomass bentonite systems analogous to deep geological repositories (DGRs) are critical to test conditions for stable engineered bentonite barrier components. This study assesses long-term temporal changes in microbial communities of compacted bentonites exposed to natural groundwater. It offers 7-year data that indicate stability of bentonite-based materials intended for use in engineered barrier systems of a DGR for the safe, long-term disposal of used nuclear fuel, with wider implications for microbial persistence in a deep subsurface environment.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".