Bibliographic record
Abstract
In this study, a Lagrangian tracking algorithm is applied to the 850-hPa relative vorticity field to characterize extratropical cyclone tracks across eastern Canada. Seasonal cycles are examined in terms of overall cyclone frequency, intensity, regions of development and decay. We found that cyclones tend to develop over the Rockies, the Great Lakes or the Western Atlantic. They are most intense over Newfoundland and North Atlantic, and decay over Greenland. Cyclones tracking across Toronto, Montreal, Halifax and St-John's are further analyzed, with typical cyclone tracks, origin, frequency, mean local growth rate, and mean intensity. Among others, we found that cyclone activities at east coast cities (Halifax, St-John's) are dominated by Atlantic cyclones, more frequent in winter, while Montreal's and Toronto's cyclones travel primarily from the Great Lakes, frequent and intense in spring and autumn. Cyclones from the Gulf of Mexico are not frequent, but extreme. The relationship between winter cyclone tracks and modes of atmospheric variability are also examined with an emphasis on the El Niño - Southern Oscillation (ENSO), North Atlantic Oscillation (NAO) and Pacific North American pattern (PNA). An ENSO and PNA-related oscillation between continental and coastal cyclones is confirmed. The inter-annual variability of winter cyclones cross eastern Canadian cities are quantified. Cyclone activities in Toronto and Montreal shown to be modulated by ENSO and PNA, while NAO dominates the cyclone variability in Halifax and St-John's. The local cyclone variability is found to be small in terms of overall cyclone statistics, but important in terms of changes in the origins of the local cyclones.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".