Reliability-Based Calibration of Region-Dependent Companion Load Combination Factors for Snow and Wind Loads in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Snow load poses substantial risks for buildings and infrastructure systems, especially in regions susceptible to significant snow accumulation. The design of building structures and infrastructure is often carried out by considering the snow load and concurrent wind load. In the present study, we carried out the reliability-based calibration of the companion load combination factors for snow and wind loads by considering the site-specific statistics of, and probabilistic models for, the snow load and concurrent wind load across Canada. The daily recorded environmental data from 222 meteorological stations were utilized in the analysis to incorporate the inherent dependency between the snow and wind loads. The calibration results were employed to recommend the region-dependent companion load combination factors, which have not been reported in the literature. Additionally, sensitivity analyses were conducted to explore the impact of return periods and probability distributions on these factors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it