Microbial Communities in Bentonite Analogues of a Deep Geologic Repository
Bibliographic record
Abstract
Investigation of life’s limitations on Earth provides the necessary information to constrain where life outside of Earth may be proliferating or previously existed. This Master’s thesis applied phospholipid fatty acid (PLFA) analysis in combination with organic carbon and 16S rRNA gene data to assess and characterize microbial communities through both microcosms and in situ samples of bentonite clay, which is an intended barrier component for the long-term storage of high-grade nuclear waste. Microcosm experiments were set up to test the impact of water activity in as-received, uncompacted bentonite clays using a high (0.99) and low (0.93) water activity over a one month period. Under aerobic incubation water activities of 0.93 and 0.99 had no resolvable effect between water activity levels on the growth of cells of indigenous communities of microbes in as-received uncompacted bentonite. Growth was detected under both water activities by a significant increase in total PLFA abundance. The increase in PLFA over the period of the study suggested an approximate increase in cells from 4x10^6 to 2x10^7 E.coli equivalent cells/g. The distribution of the PLFA and genetics data suggests the community is composed predominantly of gram-positive aerobic heterotrophs with lesser amounts of anaerobic bacteria and eukaryotes potentially in the form of fungi. Similar cell abundances and community structures were identified in the Tsukinuno Mine bentonite DGR analogue site which is a ~12 to 16 Ma deposit approximately 200 m below the surface. Total PLFA recovered from the core subsamples ranged from 32 pmol PLFA/g to 431 pmol PLFA/g, which corresponds to a range from 7.5x10^5 to 1.2x10^7 E.coli equivalent cells/g, across all cores. The community was composed of both aerobic and anaerobic bacteria consisting of gram-positive and gram-negative bacteria, as well as possible sulfate-reducing bacteria and eukaryotes.
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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 | 0.000 | 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 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".