Air Pollution Attributable Deaths: A Global View Through Fractal Analysis
Bibliographic record
Abstract
Air pollution is a global public health threat which requires in depth analysis forpolicy making. It contributes to the mortality in many urban areas. This study compares the variability of the clustered urban areas based on World Health Organization (WHO) region classified in terms of exposure to particulate matter with an aerodynamic diameter of 10 μm or less (PM10) from 2003-2010 and validated through its attributable death from 2004 & 2008. These diverse data were subjected for analysis employing fractal geometry and fractal statistics to compute its respective fractal dimensions. The purpose of such comparison is to validate a possible causative factor of the mortality. Findings revealed that the region with high variability in terms of fractal dimension in air pollution also displays more varied attributable death. This pattern is both demonstrated in all region. The paper concludes that the policies on environmental conservations in controlling air pollution and health care delivery system greatly contributes to the high fractal dimension of air pollution attributable death.
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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 | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".