Modeling the Response of Glaciers to Climate Change in the Upper North Saskatchewan River Basin
Bibliographic record
Abstract
The objective of this M.Sc. research is to quantify historical and potential future impacts of climate change on glacial contribution to streamflow in the Upper North Saskatchewan River (UNSR) basin, Alberta, Canada. The physically-based Generate Earth SYstems Science input (GENESYS) hydro-meteorological model will be used to analyze the regional impacts of historical data, and to forecast future trends in the hydrology and climatology of selected watersheds within the basin. This model has recently been successfully applied to the St. Mary River watershed, Montana, and the UNSR basin (MacDonald et al. 2009; MacDonald et al. in press; Byrne et al. in review). Hydro-meteorological processes were simulated at high temporal and spatial resolutions over complex terrain, focusing on modeling snow water equivalent (SWE) and the timing of spring melt. A glacier mass balance model is currently in development for incorporation into GENESYS to more accurately gauge the effects of climate change on glaciated areas located in the UNSR basin. General Circulation Model (GCM) scenarios will be applied to develop meaningful projections of the range of future hydrologic change under reduced glacial conditions in the basin through 2100. ABSTRACT AND INTRODUCTION GLACIERS IN THE NORTH SASKATCHEWAN BASIN
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".