A Case Study of Anomalous Snowfall with an Alberta Clipper
Bibliographic record
Abstract
An Alberta clipper moved over western New York state on 11-12 January 2004, producing snowfall amounts of up to 27 cm in portions of the region during a roughly 12-h period. In addition, lightning and thunder were reported. Such systems, known primarily for their fast motion and relatively dry nature, are not generally associated with significant snowfalls. A postmortem analysis of this event, following an ingredients-based methodology, revealed that as the weak low approached the lower Great Lakes, it came under the influence of coupled 300-hPa jets that produced enhanced divergence and significant upward vertical motion over western New York, resulting in the enhanced convective snowfall over the region for a limited time. Instability and possible enhancement via the Great Lakes are also investigated, which show that while there was at least modest instability over the region during the time of heavy snowfall, lake enhancement was unlikely.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".