Characterization of model uncertainty in predicting axial resistance of piles driven into clay
Why this work is in the frame
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Bibliographic record
Abstract
This paper summarizes 239 static load tests to evaluate the performance of four static design methods for axial resistance of driven piles in clay. The methods are ISO 19901-4:2016, SHANSEP, ICP-05, and NGI-05. The database is categorized into four groups depending on the load type (compression or uplift) and pile tip condition (open or closed end). The model uncertainty in resistance prediction is quantified as a ratio between measured and calculated resistance, which is called a model factor. The measured resistance is interpreted as a load producing a settlement level of 10% pile diameter. Database studies show that the four methods present a similar accuracy, where the mean and coefficient of variation (COV) of the model factor are around 1 and 0.3, respectively. The COV values are smaller than those for driven piles in sand available in literature. The model statistics determined from the database are applicable to a simplified or full probabilistic form of reliability-based design (RBD) of driven piles in clay. As an illustration, the resistance factors in load and resistance factor design (LRFD, a simplified form of RBD) are calibrated by Monte Carlo simulations.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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