The downstream effects of salt application on Horstman Glacier, Whistler, British Columbia
Bibliographic record
Abstract
Skiing and snowboarding occur on the seasonal snow of Blackcomb Mountain, BC, which includes two glaciers: Blackcomb Glacier and Horstman Glacier. Ski operations involve the application of salt (NaCl) to the glacier and redistribution of snow on Horstman Glacier to allow for additional skiing and snowboarding during the months of June and July. Although European studies have documented that salting ski pistes can have negative effects on the environment, no research has been conducted to study the continuous application of salt onto a glacier and the effects on the downstream aquatic environment. In this study we examined the temporal changes in chloride concentration in Horstman Creek. Using neighbouring Blackcomb Glacier and Blackcomb Creek as a reference system, automatic samplers were used to collect water samples for two periods of sixteen days each during the summer of 2008. The concentration of chloride in Horstman Creek was found to be greatly elevated compared to regional background values and those of Blackcomb Creek during both sampling periods. The pattern of chloride concentration suggests that some of the NaCl applied to the glacier makes its way downstream as initial snowmelt runoff and some is stored within the glacier and released at a later time. However, despite the fact that 90 020 kg of NaCl was applied during summer 2008, the elevated concentrations did not reach a level of environmental concern during the study period.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".