Nonlinear Failure Envelope for Microbial Induced Calcium Carbonate Precipitation Treated Sand
Bibliographic record
Abstract
Microbial induced calcium carbonate precipitation (MICP) has drawn significant attention as a more sustainable and eco-friendly ground improvement technique compared to conventional methods in recent decades. It has been shown that bio-treatment improves the shear strength of sands remarkably, and this improvement should be predictable. To predict the shear strength after bio-treatment, different types of failure envelopes with various forms can be employed. In the majority of studies on MICP-treated sands, the shear strength parameters have been calculated based on linear failure envelopes, in spite of the fact that linear failure envelopes can overestimate the shear strength at low confinements. The intercept cohesion, indeed, may be overestimated using a linear model. Therefore, this paper presents a nonlinear failure envelope which was developed based on thirteen drained triaxial tests at two levels of cementations on Ottawa 20–30 (a clean coarse sand). The obtained results indicate that nonlinear failure envelope has a higher accuracy in predicting the shear strength of MICP-treated sands at low confinements.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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".