Ground sampling program at the CANLEX test sites
Bibliographic record
Abstract
One of the primary objectives of the Canadian Liquefaction Experiment (CANLEX) project was to develop and evaluate undisturbed sampling techniques as part of the overall goal to focus and coordinate Canadian geotechnical expertise on the topic of soil liquefaction. Six sites were selected by the CANLEX project in an attempt to characterize various deposits of loose sandy soil. The sites consisted of a variety of soil deposits, including hydraulically placed sand deposits associated with the oil sands industry, natural sand deposits in the Fraser River Delta, and hydraulically placed sand deposits associated with the hard-rock mining industry. At each site, a target zone was selected and various methods of ground sampling were performed. These included ground freezing and sampling, fixed piston tube sampling, Christensen double-tube core sampling, large-diameter sampling using the Laval sampler, and sonic (rotary-vibratory) continuous coring. Ground freezing and sampling was performed at all six sites; the other methods were used at only some sites. Geophysical (gamma-gamma) logging was also performed in boreholes near the freeze pipe to independently measure in situ void ratios. This paper describes the techniques used in the ground-freezing and various sampling programs and presents a summary of the results. Comparisons of void ratios measured for various types of samples and using geophysical logging are also made.Key words: CANLEX, ground freezing, sampling, geophysical logging, void ratio.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".