Bibliographic record
Abstract
Do Geomagnetic disturbances drive homicide rates in the USA Canada? We all know it takes two to tango, what we did not know was that there were others dancing tango along the same longitude, until the Sun pulled the trigger. Beltrão, Almeida and I recently published an article suggesting Solar storms may drive homicides rates across the Atlantic. Because the geomagnetic impact of solar storms may last only a few hours, it would also be interesting to see what happens in countries with reliable homicide data and on the same longitude, meaning simultaneously exposed to the same solar storms. This is why we chose to compare the homicide rates of the USA and Canada. The importance and disparity in structural factors between Canada and the USA, like values, gun ownership, and income inequality, suggest that USA homicide rates should be higher than Canadian ones, and on average they are over three times higher for the period 1990-2020. Nothing new up to here. What is startling is that between 1990 and 2020 homicide rates in the USA and Canada evolved in tandem, with a correlation of 90%!
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.025 |
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".