Novel non-nuclear methodology for coarse granular soil compaction control: the Sherbrooke Method
Bibliographic record
Abstract
The nuclear density gauge (NDG) is the most established device for compaction control. Several studies have proposed alternatives to it, but none have been widely adopted for a variety of reasons. This paper presents the Sherbrooke Method (SM), which involves the use of innocuous, user-friendly, and low-cost devices. It uses frequency domain reflectometry (FDR) sensors to obtain bulk density and gravimetric water content. In this research, 442 field test comparisons between the SM and the NDG device, and 117 between the SM and physical tests were obtained at sites where a type of well-graded gravel (MG 20 in Quebec) was used. The FDR technology showed promising results, with good ability to predict bulk density and gravimetric water content. Moreover, the method presented low complexity of execution and the data emitted by the probe can be obtained in 1 minute. Nowadays, the total lapse of time from setting up the device to the final response (of 3 tests) is approximately 20 minutes. The SM also presents a bulk density precision comparable to that of other devices reported in the technical literature.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".