Grading model for fine soil classification using cone penetration testing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The grading of fine-grained soils is one of fundamental properties, and studying how to obtain this information using in situ methods is essential. However, existing cone penetration tests (CPT) lack a direct approach for measuring particle size and its content. To address that issue, the relationship between cone tip resistance ( q c ) and sleeve friction resistance ( f s ) with these curve parameters (CPs) was established using in situ CPT. Finally, an expression for the grading curves based on the results obtained from the CPT was presented. The main conclusions are as follows: (1) An exponential relationship exists between fine content and the variation pattern of fitting parameters used to characterize the grading curve, depending on the soil layer type. (2) The depth-corrected CPs are related to the q c and f s by a power function, revealing a link between the CPT and grading curve; (3) by utilizing global CPT and soil layer data, the boundaries of CPs were precisely defined, and the content of different particle sizes across various soil layers was predicted. The applicability of the fitting results was then analyzed for both homogeneous fine-grained soils and complex soil type.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it