Properties and Behavior of Sandy Soils by a New Interpretation of MICP
Bibliographic record
Abstract
Research on MICP technology for ground improvement began in the early 2000s, and since then, it has been considered as innovative research. The field of applications is showing signs of expanding from sandy soil stabilization to remediation. However, the research has not always progressed, because it is extremely difficult to evaluate the ability (viability rate) related to microorganisms and how to handle them quantitatively. In fact, this problem hinders the consensus of research results in terms of quantitative evaluation of microorganisms and the cross-comparison (evaluation) and use of MICP technology research. The crucial disadvantage of using bacteria is that their properties are not constant due to changes over time and in the surrounding environment. Therefore, for engineering purposes, we used the carbonate formation rate (CPR), instead of urease activity, as a function of the microbial mass (OD) with viable bacteria. Thus, the standard OD−CPR relationship was defined experimentally, and the estimation method of viability was established. The required amount of microorganisms for testing was given by OD*, and the relationship “OD = Rcv OD*” was defined to convert from OD* to OD. Rcv was defined as the viable bacterial rate. It was found that the Ca2+/OD ratio controls the inhibition behavior in MICP. At a Ca2+/OD ratio of >8.46 M, then inhibition occurs, while at Ca2+/OD = 8.46 M, CPR = 8.46 OD and the CPR is proportional to the viable OD, Rcv, and OD*. We show that it is possible to perform an experiment using OD* with aged bacteria, obtain Rcv from the standard OD−CPR and OD*−CPR relationships, convert OD* to OD and to perform a unified evaluation without actually determining the viability rate.
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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 | 0.001 | 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".