Autumn synoptic conditions and rainfall in the subarctic Canadian Shield of the Northwest Territories, Canada
Bibliographic record
Abstract
Autumn precipitation is important to the annual water budget and spring streamflow magnitude in the subarctic Canadian Shield portion of the Mackenzie Basin in northwestern Canada. The objective of this study is to improve understanding of the synoptic mechanisms generating this autumn precipitation by investigating a wet (1998) and a dry (1999) autumn over a portion of this region north of Great Slave Lake. Seven synoptic map patterns were identified using a hybrid manual–revised Kirchhofer correlation methodology. Cyclones were found to be the most important map pattern providing autumn rainfall. These cyclones tend to occur 2 to 3 days following the presence of a low in the Gulf of Alaska near the Aleutian Islands. The results of this study corroborate past research that shows Pacific atmospheric moisture transported inland provides the source for much of the cyclonic rainfall in the Mackenzie Basin. Aleutian lows, which encourage this transportation, were as common in 1998 as in 1999, but the mechanisms necessary to transfer moisture to the North Great Slave region were more entrenched in 1998 than in 1999. Winds along storm tracks through the region were weaker and more dispersed in 1999. In addition, conditions for cyclogenesis in the region were less favourable in 1999. Copyright © 2005 Royal Meteorological Society
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 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".