Application of Biobarriers for Groundwater Containment at Fractured Bedrock Sites
Bibliographic record
Abstract
Abstract Biological barriers are a beneficial application of biofilms that aim at reducing the hydraulic conductivity (K) in geological formations. Several studies have shown the potential benefits of creating such barriers either by stimulating the indigenous microbial community (biostimulation) or injecting bacteria (bioaugmentation). For example, laboratory experiments show that groundwater microorganisms attached to a ceramic surface and generated a biofilm as thick as 1,100 μm. In a limestone fracture, this bacterial community clogged a single fracture up to 99.2 percent within 22 days. At the field scale, applications in porous aquifers led to a five‐fold decrease in K after 2.5 days of biostimulation, and a bioaugmentation with a starved, adapted bacterial culture decreased K by 99.4 percent. One promising development of the biobarrier concept is a field application at a fractured bedrock site. Using a multidisciplinary approach and focusing on a well‐characterized fracture system, a field trial was undertaken in Southern Ontario to measure the extent of bioclogging and the stability over time. This article focuses on the literature pertinent to the preparation of this field trial and presents the innovative approach selected to monitor the bioclogging in such a challenging 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".