Practical method for determining load and resistance factorsusing third-moment transformation
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Bibliographic record
Abstract
Load and resistance factor design (LRFD) is a suitable format for the reliability-based limit state design of structures. It has been adopted in many countries, such as the United States, Europe, Canada, and Japan. Usually, the first-order reliability method (FORM) is used to estimate the load and resistance factors, but it requires the determination of design points and complicated double iterative computations. Therefore, FORM is not easy or practical for engineers to use. This paper presents a simple, accurate method to determine the load and resistance factors utilizing the third-moment transformation, which does not require derivative-based iterations and can estimate the load and resistance factors without using the distribution of random variables. In addition, the proposed method provides enough accurate results within a wide range of target reliability indices. Therefore, this method should be effective and convenient for calculating the load and resistance factors in actual practice. Five numerical examples illustrate the proposed method's efficiency and accuracy; FORM provides a benchmark for comparison.
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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 | 0.001 | 0.002 |
| 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