Establishing Heat Alert Thresholds for the Varied Climatic Regions of British Columbia, Canada
Bibliographic record
Abstract
Following an extreme heat event in 2009, a Heat Alert and Response System (HARS) was implemented for the greater Vancouver area of British Columbia (BC), Canada. This system has provided a framework for guiding public health interventions and assessing population response and adaptation to extreme heat in greater Vancouver, but no other parts of BC were covered by HARS. The objective of this study was to identify evidence-based heat alert thresholds for the Southwest, Southeast, Northwest, and Northeast regions to facilitate the introduction of HARS across BC. This was done based on a national approach that considers high temperatures on two consecutive days and the intervening overnight low, referred to as the high-low-high approach. Daily forecast and observed air temperatures and daily mortality counts for May through September of 2004 through 2016 were obtained. For each date (dayt), dayt−2 forecasts were used to assign high temperatures for dayt and dayt+1 and the overnight low. A range of high-low-high threshold combinations was assessed for each region by finding associations with daily mortality using time-series models and other considerations. The following thresholds were established: 29-16-29 °C in the Southwest; 35-18-35 °C in the Southeast; 28-13-28 °C in the Northwest; and 29-14-29 °C in the Northeast. Heat alert thresholds for all regions in BC provide health authorities with information on dangerously hot temperature conditions and inform the activation of protective public health interventions.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".