Estimating and Mapping Extreme Ice Accretion Hazard and Load Due to Freezing Rain at Canadian Sites
Bibliographic record
Abstract
Abstract The ice accretion load in Canadian structural design codes is developed based on an operational ice accretion prediction model. In the present study, three models are employed to predict the ice accretion amount on a flat surface and horizontal wire at Canadian sites. The results confirm that the model used by Canadian practice for predicting ice accretion leads to a conservative estimate as compared to the remaining two models. The results also indicate that the use of the Gumbel distribution for the annual maximum ice accretion is adequate for regions prone to ice accretion and that the lognormal distribution may be considered for regions with a moderate or negligible amount of ice accretion. Maps of the ice accretion hazard at five selected Canadian sites are developed. Statistical analysis of an equivalent wind speed that is concurrent with the iced wire is carried out, showing that the concurrent wind speed for the 50-year return period value of the annual maximum ice accretion amount is smaller than the 50-year return period value of the annual maximum wind speed. It is shown that the statistical characteristics of the annual maximum concurrent wind speed on iced wire differ from that of the annual maximum wind speed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".