Why is there a discrepancy in shear wave velocity – cone tip resistance (<i>V</i><sub>s</sub>–<i>q</i><sub>c</sub>) correlations’ trends with respect to grain size?
Bibliographic record
Abstract
Although many regression equations of cone penetration test tip resistance, qc-CPT, versus shear wave velocity, Vs, are available in the literature resulting from a substantial research effort in this topic area, the outcome of these research efforts with respect to the influence of grain size on the Vs–qc correlations is in fact inconclusive because some of the suggested relationships, in common use today, either utilize irrelevant parameters or they are rather crude approximations of the Vs–qc trend over a wide range of grain sizes. A closer examination of this effect would be important for better assessment of the reliability and limitations of the proposed correlations. This note discusses the plausible reasons for the inconsistency in the existing Vs–qc correlations with respect to grain size through a detailed comparison of two well-known discrepant correlations referring to comparable experimental and field data. This note then goes further in its contribution to the practice of geotechnics by providing some useful recommendations to be considered in the prospective construction of Vs–qc correlations, especially when particle characteristics are taken into account.
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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 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".