The Correlation between U.S. Tornadoes and Pacific Sea Surface Temperatures
Bibliographic record
Abstract
The correlation between tornadic activity in several regions of the United States and the monthly mean sea surface temperature over four zones in the tropical Pacific Ocean is examined. Tornadic activity is gauged with two mostly independent measures: the number of tornadoes per month, and the number of tornadic days per month. Within the assumptions set forth for the analysis, it is found that there appears to exist a statistically significant but very weak correlation between sea surface temperature in the Pacific Ocean and tornadic activity in the United States, with the strength and significance of the correlation depending on the coordinates at which the sea surface temperatures are assessed and the geographic region of the United States. The strongest evidence found is for the correlation between the number of days with strong and violent (F2 and greater) tornadoes in an area that runs from Illinois to the Atlantic Coast, and Kentucky to Canada and a cool sea surface temperature in the central tropical Pacific. However, there is only about a 53% chance of this relationship occurring in a specific month.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".