Estimating the number of excess deaths attributable to heat in 297 United States counties
Bibliographic record
Abstract
There is a well-established relationship between high ambient temperature and risk of death. However, the number of deaths attributable to heat each year in the United States remains incompletely quantified. METHODS: We replicated the approach from a large, international study to estimate temperature-mortality associations in 297 United States counties and additionally calculated the number of deaths attributable to heat, a quantity of likely interest to policymakers and the public. RESULTS: Across 297 counties representing 61.9% of the United States population in 2000, we estimate that an average of 5,608 (95% empirical confidence interval = 4,748, 6,291) deaths were attributable to heat annually, 1997-2006. CONCLUSIONS: Our results suggest that the number of deaths related to heat in the United States is substantially larger than previously reported.
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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 | 0.000 |
| 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) | 0.004 | 0.001 |
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; both teacher heads agree on what is shown here.
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".