Evaluation of Alberta Hail Growth Model Using Severe Hail Proximity Soundings from the United States
Why this work is in the frame
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Bibliographic record
Abstract
Abstract A one-dimensional, coupled hail and cloud model (HAILCAST) is tested to assess its ability to predict hail size. The model employs an ensemble approach when forecasting maximum hail size, uses a sounding as input, and can be run in seconds on an operational workstation. The model was originally developed in South Africa and then improved upon in Canada, using high quality hail verification data for calibration. In this study, the model was run on a spatially and seasonally diverse set of 914 modified severe hail proximity soundings collected within the contiguous United States between 1989 and 2004. Model output was then compared to the maximum observed hail size for each proximity sounding. Basic verification statistics are presented, showing that the HAILCAST model exhibits considerable skill that can be of use to the operational severe weather forecaster.
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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 it