Uncovering Canada’s True Tornado Climatology: Inside The Northern Tornadoes Project
Bibliographic record
Abstract
ornadoes have resulted in a number of historic catastrophes in Canada.Saskatchewan's Regina "cyclone" of 30 June 1912 left 30 dead and hundreds injured.On 17 June 1946, parts of Windsor, Ontario, were devastated by an F4 tornado, 1 resulting in 17 deaths and close to 100 injuries.While much farther north, Edmonton, Alberta, did not escape a tornado's wrath on 31 July 1987 when an F4 tornado killed 27, injured hundreds, and caused extensive damage.Although tornadoes have been verified in every province and territory in Canada, most have been recorded in the southern Prairies and southern Ontario, regions with some of the country's largest urbanized areas, and high population densities.Intense thunderstorms are known to occur in large, sparsely populated areas of Canada, but tornado reports are rare.This results in considerable gaps in our understanding of the nation's tornado climatology.Statistical modeling using tornado observations, lightning data, and population density as inputs has suggested that only ~45% of Canada's tornadoes are verified.Also, a national maximum was predicted in Adapted From "The Northern Tornadoes Project: Uncovering Canada's True Tornado Climatology," by
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".