A new index for the verification of accuracy and timeliness of weather warnings
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT A new scoring index is proposed for the verification of the C anadian weather warning program. Called weather warning index ( WWI ), the new measure is designed to be sensitive to two attributes of warnings, their timeliness and accuracy, and to summarize the verification information into a single value for a representative set of regions of C anada and for several weather elements for which warnings are issued. Given the opposing nature of the two attributes (long lead times are likely to be associated with lower accuracy), it was necessary to carefully balance the score to keep it proper in a general sense. The design decisions for the WWI are presented and discussed, and the score computation is illustrated with sensitivity experiments using 3 years of warning forecasts and observations. Copyright © 2013 Royal Meteorological Society
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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 | 0.000 | 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 | 0.000 |
| 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 it