Weather systems occurring over Fort Simpson, Northwest Territories, Canada, during three seasons of 1998–1999: 2. Precipitation features
Bibliographic record
Abstract
Precipitation events were examined at Fort Simpson, Northwest Territories, Canada, during the autumn and winter of 1998 and during the spring of 1999 with a variety of observational tools, including a polarimetric radar. This location is characterized by a relatively small amount of precipitation (annual average of 450 mm), with approximately half being in the form of snow. During the observational periods, precipitation was produced within multilayered cloud systems with heights ranging up to 10 km, and instances of light snow were associated with either low (<2.5 km) or high (up to 10 km) clouds. Precipitation over the observational periods was typically produced in banded structures, was sometimes reduced because of subcloud evaporation or sublimation, and in the winter was often in the form of individual crystals. A state‐of‐the‐art weather forecasting model was often poor at simulating some of the critical features of the precipitation events, such as cloud top height and precipitation amount. In addition, it was shown that with the sensitive CloudSat radar, ∼17% of overpasses will be associated with the occurrence of detectable precipitation at Fort Simpson, but with the less sensitive Global Precipitation Measurement (GPM) radar, much of the precipitation will be undetected.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".