Practical Considerations when Using the Swedish Fall Cone
Bibliographic record
Abstract
Abstract This paper presents the results of Swedish fall cone tests and Casagrande liquid limit tests conducted on saline Champlain Sea clay samples from Lachenaie, Quebec. The main objective was to study a few hitherto unanswered practical questions regarding these testing methods. Penetration range is found to affect the Hansbo’s relationship used in fall cone experiments, while the mass and the bluntness degree of the cone have no effect on it. A direct relationship between thixotropic regain in shear strength and sensitivity is found. When measuring the liquid limit, if only the first penetration depth is recorded, results are up to 5 % smaller than those obtained when following the standard procedure of CAN/BNQ-2501-092. With this standard, the average of the first two penetration depths within 0.3 mm of each other is recorded. These penetrations usually follow the bulk of the thixotropic shear strength regain. The Swedish fall cone was compared to the traditional Casagrande apparatus for liquid limit determinations. The two methods yielded identical results in the studied conditions (saline Lachenaie clay with liquid limit between 44% and 75%). An incorrect calibration of the height-of-drop of 1.4 mm led to a mean error of 6 liquid limit points. This error is greater than the theoretical error obtained by assuming that the number of blows is proportional to the square of the height-of-drop.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".