Calibration of PET strap pullout models using a statistical approach
Bibliographic record
Abstract
Polyester (PET) straps are being used more frequently in mechanically stabilized earth (MSE) walls. At present, there is no consensus on a model or models that are suitable for design codes to calculate the pullout capacity of these materials. A database of 296 pullout tests from 81 test series with single and closely-spaced parallel double PET strap configurations was collected by the writers. The data were taken from laboratory and in situ pullout tests. Existing linear and bi-linear pullout models for geosynthetic and steel strip reinforcement were investigated as candidate models and then empirically modified to improve pullout capacity predictions for both single and double PET strap arrangements. A non-linear exponential model with the same number of empirical coefficients was also investigated. The accuracy of each model was assessed quantitatively using bias analysis where bias is the ratio of measured to predicted capacity. The paper shows that non-linear models performed best based on mean and coefficient of variation (COV) of bias values and bias dependency with predicted pullout capacity and magnitude of vertical stress acting on the pullout length. The models investigated in this study are useful for pullout limit state calculations using both deterministic and reliability-based analysis and design approaches.
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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 | 0.000 | 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 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".