Bibliographic record
Abstract
The current issue of Eurosurveillance updates and provides additional context to the report in early 2004 of an estimated 22 080 excess deaths in England and Wales, France, Italy and Portugal during and immediately after the heat waves of the summer of 2003 [1]. While estimates for England and Wales [2], France [3], and Portugal [4], are largely unchanged from those reported earlier, to these should be added 6595-8648 excess deaths in Spain [5], of which approximately 54% or 3574-4687 occurred in August, and 1400-2200 in the Netherlands [6], of which an estimated 500 occurred during the heat wave of 31 July-13 August. Data for Italy, provided here for the cities of Bologna, Milan, Rome, and Turin, are compatible with the earlier estimate that 3134 excess deaths occurred in the 21 Italian regional capitals during the period 1 June-15 August [1,7]; the Italian National Institute of Statistics however, reported an excess of 19 780 deaths country-wide during June-September 2003 as compared to 2002 [8]. Reports elsewhere indicate that approximately 1250 heat-related deaths occurred in Belgium during the summer of 2003 [9], that there were 975 excess deaths during June-August in Switzerland [10] and 1410 during the period August 1-24 in Baden-Württemberg, Germany [11]. At this point, it seems reasonable to speculate that with evidence of heat wave-associated deaths beyond England and Wales, France, Italy, and Portugal, the previously published estimate of 22 080 early August excess deaths should be revised upward by at least 50% for all of western Europe, and by 100% or more if heat events that occurred during June and July 2003 are also taken into account.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.011 |
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".