Derivation of an adjustment factor map for the estimation of the water equivalent of snowfall from ruler measurements in Canada
Bibliographic record
Abstract
This paper provides an updated fresh snowfall water equivalent adjustment factor (ρswe) map for Canada to allow the estimation of solid precipitation amount from ruler measurements of the depth of freshly fallen snow, which has been the standard method for measuring snowfall since Canadian climate measurements began in the middle of the nineteenth century. The ρswe map is created based on the comparison of corrected solid Nipher gauge precipitation to snowfall ruler depth measurements at 175 stations with more than 20 years of concurrent observations. The Nipher gauge correction process involved a careful analysis of station metadata to obtain precise information on anemometer heights and the dates that Nipher gauges were activated. The updated fresh snowfall water equivalent adjustment factor map allows estimates of ρswe to be obtained for all long‐term climate stations in Canada. The spatial pattern is consistent with processes influencing the density of fresh snowfall and its initial settling with values ranging from more than 1.5 over the Maritimes to less than 0.8 over southern‐ central British Columbia.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".