Construction Considerations for ISS Bench-Scale Studies and Field-Scale Monitoring Programs
Bibliographic record
Abstract
In situ solidification/stabilization (ISS) projects require a significant amount of characterization, sampling, and bench-scale testing in the design or feasibility phase to ensure a successful project. During this phase the proposed construction methods need to be considered, taking into account such things as slurry proportions, untreated soil type/density, treated soil consistency, and soil/contaminant variability. As the project moves from the preconstruction phase into the construction phase, the results of the design phase are used to refine key project objectives which may include target improvements for permeability, strength, and/or leachability. A quality control/quality assurance monitoring program, which may include a combination of process controls, in-situ testing, and laboratory testing on grab samples, is then developed to confirm that the key project objectives are achieved. Process controls provide immediate feedback but generally do not directly measure the target properties. Many of the available in situ testing methods were not developed for ISS mixtures and are therefore limited for use in this application. Finally, many of the laboratory tests conducted on field collected grab samples, specifically leachability tests, require long lead times and therefore provide limited real-time feedback. In order to account for the advantages and disadvantages of each monitoring method, the quality control/quality assurance monitoring program should include a combination of short and long turnaround testing to be used collectively to predict the long-term performance of the improved material.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".