Bibliographic record
Abstract
A number of extreme value analysis techniques are utilised to predict basic design gust wind speeds for Fiji, which lies in a tropical cyclone prone region. The study shows that a number of modern methods tend to highly under-predict extreme wind speeds in regions of Fiji severely affected by tropical cyclones, although their skills improve in less severely affected regions. The reference for comparison was Dorman’s method, which has been previously used as a guidance for development of Region D wind speeds in the Australian wind loading code – the AS1170.2-1989. In the case of Fiji, this study recommends the AS1170.2-1989 Region C provisions for Suva and the eastern coasts of the main island of Viti Levu only, and the AS1170.2-1989 Region D provisions elsewhere. This is significantly different to the provisions of the current National Building Code of Fiji (1990) which allow for the use of AS1170.2-1989 Region C provisions for all of Fiji. This difference is attributed to differences in the frequency and intensity of tropical cyclones visiting Fiji as compared with those for Australian Region C.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".