Association of Geomagnetic Disturbances and Suicide Attempts in Taiwan, 1997–2013: A Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: A previous study in Japan found that monthly mean K index values were related to the monthly number of male, but not female, suicides. Correlations between geomagnetic disturbances and suicide/depression have also been reported in countries such as Canada, South Africa, Finland, Australia, Russia, and Japan. We have previously shown that stronger geomagnetism is linked to a higher standardized mortality ratio for suicide. To date, however, no published studies have reported the correlation between geomagnetic disturbances and suicide attempts in Taiwan. METHODS: Data on the monthly number of suicide attempts in Taiwan from January 1997 to December 2013 were obtained. We performed a multivariable analysis, with the number of suicide attempts as the response variable and monthly Kp10 index, F10.7 index, sulfur dioxide, carbon monoxide, ozone, fine particulate matter (PM2.5), temperature, humidity, unemployment rate, and cosmic rays as the explanatory variables. RESULTS: The multivariable analysis showed that Kp10 index, temperature, humidity, unemployment rate, and cosmic rays were associated with the number of male suicide attempts and that Kp10 index, F10.7 index, carbon monoxide, temperature, humidity, and unemployment rate were associated with the number of female suicide attempts. CONCLUSION: This is the first article reporting statistically significant relationships between the monthly number of male and female suicide attempts and the monthly mean Kp10 value in Taiwan.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".