Numerical Analysis of CPT Results for Thin Layer and Transition Effects
Bibliographic record
Abstract
Many research works have proved that CPT results (especially the cone resistance, 𝑞 𝑐 ) are not only a function of the properties of the soil in which the cone is located, but also the layers ahead and behind that. in this paper, using series of numerical simulations, variations of 𝑞 𝑐 in a multiple-layered soil with sharp borders were studied.The model consisted of a 50-to 300-mm-thick layer of soft fine grained soil embedded in dense coarse grained layers.The ratio of the moduli of elasticity of the soft to dense soils, 𝑅 𝑠 , ranged from 0.042 to 0.833.The transition zones (the distances above and below the soft layer over which the 𝑞 𝑐 is affected) were analyzed as a function of ℎ 𝑠 and 𝑅 𝑠 .Further, a method was introduced to capture and backcalculate the actual 𝑞 𝑐 from the measured values.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".