Spatial Autocorrelation, Source Water and the Distribution of Total and Viable Microbial Abundances within a Crystalline Formation to a Depth of 800 m
Bibliographic record
Abstract
Proposed radioactive waste repositories require long residence times within deep geological settings for which we have little knowledge of local or regional subsurface dynamics that could affect the transport of hazardous species over the period of radioactive decay. Given the role of microbial processes on element speciation and transport, knowledge and understanding of local microbial ecology within geological formations being considered as host formations can aid predictions for long term safety. In this relatively unexplored environment, sampling opportunities are few and opportunistic. We combined the data collected for geochemistry and microbial abundances from multiple sampling opportunities from within a proposed host formation and performed multivariate mixing and mass balance (M3) modelling, spatial analysis and generalized linear modelling to address whether recharge can explain how subsurface communities assemble within fracture water obtained from multiple saturated fractures accessed by boreholes drilled into the crystalline formation underlying the Chalk River Laboratories site (Ontario, Canada). We found that three possible source waters, each of meteoric origin, explained 97% of the samples, these are: modern recharge, recharge from the period of the Laurentide ice sheet retreat (ca. ~12000 years before present) and a putative saline source assigned as Champlain Sea (also ca. 12000 years before present). The distributed microbial abundances and geochemistry provide a conceptual model of two distinct regions within the subsurface associated with bicarbonate -- used as a proxy for modern recharge -- and manganese; these regions occur at depths relevant to a proposed repository within the formation. At the scale of sampling, the associated spatial autocorrelation means that abundances linked with geochemistry were not unambiguously discerned, although fine scale Moran’s eigenvector map (MEM) coefficients were correlated with the abundance data and suggest the action of localised processes possibly associated with the manganese and sulfate content of the fracture water.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".