Wind turbines and health: An examination of a proposed case definition
Bibliographic record
Abstract
Renewable energy demands have increased the need for new wind farms. In turn, concerns have been raised about potential adverse health effects on nearby residents. A case definition has been proposed to diagnose "Adverse Health Effects in the Environs of Industrial Wind Turbines" (AHE/IWT); initially in 2011 and then with an update in 2014. The authors invited commentary and in turn, we assessed its scientific merits by quantitatively evaluating its proposed application. We used binomial coefficients to quantitatively assess the potential of obtaining a diagnosis of AHE/IWT. We also reviewed the methodology and process of the development of the case definition by contrasting it with guidelines on case definition criteria of the USA Institute of Medicine. The case definition allows at least 3,264 and up to 400,000 possibilities for meeting second- and third-order criteria, once the limited first-order criteria are met. IOM guidelines for clinical case definitions were not followed. The case definition has virtually no specificity and lacks scientific support from peer-reviewed literature. If applied as proposed, its application will lead to substantial potential for false-positive assessments and missed diagnoses. Virtually any new illness that develops or any prevalent illness that worsens after the installation of wind turbines within 10 km of a residence could be considered AHE/IWT if the patient feels better away from home. The use of this case definition in the absence of a thorough medical evaluation with appropriate diagnostic studies poses risks to patients in that treatable disorders would be overlooked. The case definition has significant potential to mislead patients and its use cannot be recommended for application in any health-care or decision-making setting.
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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 | 0.075 | 0.155 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.011 | 0.006 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.008 | 0.008 |
| 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; 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".