Synoptic controls on the surface energy and water budgets in sub-arctic regions of Canada
Bibliographic record
Abstract
An objective hybrid classification of daily surface weather maps for central and western Canadian sub-arctic locations was used to determine their dominant synoptic conditions during the snow free period. This classification yielded seven dominant synoptic types for each location during the snowmelt and snow-free periods (20 April–7 September), accounting for ∼90% of the days in period. The effects of source regions were used to explain the observed air mass characteristics, and their influence on the respective study locations. Cooler, drier air masses were the most frequent at both study locations. Arctic high pressure cells to the northeast brought the coolest air to the western sub-arctic site, Trail Valley Creek (TVC), Northwest Territories, while high pressure systems approaching from the northwest brought the coolest conditions to the central sub-arctic site, Churchill, Manitoba. Sub-tropical high pressure approaching from the west–southwest brought warm air to TVC, whereas stationary high pressure to the south warmed Churchill. These synoptic regimes exerted strong controls on the precipitation and evaporation components of the water balance as observed in terms of cloud cover, radiation and precipitation and evaporation efficiencies. Copyright © 2000 Royal Meteorological Society
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".