Interdisciplinary Analysis of Annual Space Weather Activity in Relation to Mortality Associated with Cerebrovascular Disease: A Novel Model of Solar-Terrestrial Interaction
Bibliographic record
Abstract
A combination of heliobiological and biometeorological perspectives on human biology and epidemiology has recently yielded many intriguing results suggesting relationships with various measures of space weather. The convergence of empirical results with quantitative dimensional analyses has also proven incredibly effective in explaining similar results and in constructing new models of solar-terrestrial interaction. In the current study, we applied these approaches to the analysis of annual mortality rates associated with cerebrovascular diseases in Canada from 1979 to 2009 to determine potential overlap with our previous work on hypertensive disease mortality with heliogeophysical factors and derive values for constructing a novel model of solar influence on terrestrial biology. Annual cerebrovascular disease mortality displayed a strong non-linear trend over time. As suspected, correlation analyses with various measures of solar, geomagnetic, and cosmic ray features suggested a significant relationship between cerebrovascular mortality and the plasma beta function for solar wind pressures which was phase shifted by ~5 to 6 years. After removing a fourth-order polynomial trend from cerebrovascular data, the dominant cycle demonstrated was ~14.60 years, offset from the ~10.90 year cycle of the average plasma beta by approximately 6 years. Finally, we employed relevant values from these results for dimensional analysis using physical constants from physics, neuroscience, and astronomy in order to help describe an Earth-Sun circuit connected by magnetic flux lines through which pressure waves might propagate, resulting in a lagged or cumulative influence on cerebrovascular-related death.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".