Scalp-and-Replacement of Oversize Particles: Laboratory Permeameter Testing
Bibliographic record
Abstract
Abstract A reanalysis is made of 24 rigid-wall permeameter tests on eight widely-graded sand-gravel mixtures, using empirical methods that post-date the original study by Jones in 1955. The reanalysis is conducted to better understand the consequences of the scalp-and-replacement method of removing oversize particles in laboratory permeameter testing. A necessary requirement of the scalp-and-replacement method is that the porosity, hydraulic conductivity, and susceptibility of the test gradation to internal instability be largely unchanged. The reanalysis provides a framework for such considerations and serves to identify the consequences of excessive scalping such as increased porosity and hydraulic conductivity. The results show that scalp-and-replacement to 35 % of the gradation curve imparts no significant change to the porosity and hydraulic conductivity of an internally stable gradation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".