Climate Change and the Monitoring of Vector-borne Disease
Bibliographic record
Abstract
PREDICtion, little noted at the time, that anthropogenic emissions of carbon dioxide would trap the radiative energy of the sun within the earth's atmosphere and raise surface temperatures. 1 An early investigation of this "greenhouse effect" concluded that a "large-scale geophysical experiment" began ever since the Industrial Revolution wed civilization to fossil fuels. 2 The recent data of several international consortia show that global warming is accelerating at a rate far greater than that predicted a century ago and is due in large part to combustion of fossil fuels. 3 This issue of MSJAMA brings together several lines of published evidence that global warming has emerged as a public health challenge requiring serious, concerted action.Jonathan Patz and Mahmooda Khaliq survey the immediate threats posed by climate change as well as some of the more insidious ones.Kent Bransford and Janet Lai find grounds for a common approach to both climate change and air pollution.Stephen Liang and colleagues describe technologies that can help track the spread of climate-sensitive infectious disease vectors.Finally, William Burns discusses public policy tools to respond and adapt to these challenges.Unfounded alarmism has no place either in clinical practice or in the legislative process.On the other hand, we cannot simply ignore extensive, peer-reviewed data on the causes and impacts of climate change.Lending a sense of urgency to this seemingly distant and abstract threat may well require us to link its consequences to our quality of life.In the absence of domestic leadership on global warming, one way to accomplish this goal might be to summon health care professionals to nontraditional advocacy roles.A similar approach helped give birth to the Montreal Protocol of 1987.Parties to the convention that produced the treaty identified depletion of the UV-absorbing ozone layer by chlorofluorocarbons (CFCs) as a public health threat of potentially catastrophic proportions requiring immediate action, namely, the phasing out of CFCs and related compounds. 4 A role for health care professionals in global environmental policy is a natural extension of a growing ethos of preventive medicine, the sort that has, for instance, reduced the prevalence of smoking in the United States and led to improvements in food, highway, and gun safety.Similarly, it is not too late and none too soon for the health care community to advocate policies that wean us from fossil fuels and ultimately mitigate the extent of human-induced climate change.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".