A Diagnostic Examination of the Eastern Ontario and Western Quebec Wintertime Convection Event of 28 January 2010
Bibliographic record
Abstract
Abstract The priority of an operational forecast center is to issue watches, warnings, and advisories to notify the public about the inherent risks and dangers of a particular event. Occasionally, events occur that do not meet advisory or warning criteria, but still have a substantial impact on human life and property. Short-lived snow bursts are a prime example of such a phenomenon. While these events are typically characterized by small snow accumulations, they often cause very low visibilities and rapidly deteriorating road conditions, both of which are a major hazard to motorists. On the afternoon of 28 January 2010, two such snow bursts moved through the Ottawa River valley and lower St. Lawrence River valley, and created havoc on area roads, resulting in collisions and injuries. Using the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR), these snow bursts were found to be associated with an approaching strong upper-tropospheric trough and the passage of an arctic front. While convection or squall lines are not common in January in Canada, snow bursts are shown to be associated with strong quasigeostrophic forcing for ascent and low-level frontogenesis, in the presence of both convective and conditional symmetric instability. Finally, this paper highlights the need for the development of a standard subadvisory criterion warning of short-lived but high-impact winter weather events, which operational forecasters can issue and quickly disseminate to the general public.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.003 | 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".