Efficiency of Biocementation as Rock Joints Sealing Technique Evaluated Through Permeability Changes
Bibliographic record
Abstract
In Microbially Induced Carbonate Precipitation (MICP), bacteria are used to hydrolyze urea.In the presence of a calcium source supplied in a feeding solution, calcium carbonate is formed and precipitates.MICP has shown promising results in terms of improving the hydro-mechanical properties of sandy soils by forming bonds connecting the particles.Recent studies are focused on using MICP for sealing discontinuities, such as concrete and stone cracks, and rock joints.This is investigated in this paper for a diskshaped rock sample having a crack along the entire diameter.In the study presented, enzyme is used instead of bacteria, because prior studies proved that production of calcium carbonate is faster while using enzyme.In addition, large quantities of enzyme required for Civil Engineering applications can be produced easier comparing to bacteria, and for this reason, using enzyme may be an alternative to using bacteria.The efficiency of the method was evaluated by constant head water permeability test during the treatment.The permeability of the crack reduced along time and the crack was almost completely sealed after 6 hours of treatment.Upon completion of the treatment, the crack was investigated visually to detect the presence of precipitated biocement.
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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 | 0.000 | 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".