A hydrological approach to estimating daily glacier ablation
Bibliographic record
Abstract
Reduced meltwater discharge owing to glacier retreat can have severe impacts on downstream water users. To assess these impacts, it is essential to differentiate between water from glacier melt and other sources. We propose a method for doing this on a daily time scale by applying a mixing law to electrical conductivity and proglacial discharge measurements. Daily ablation is then estimated by applying a recession law to the glacier melt component. Testing this method on summer hydrology and meteorology measurements from the Baounet Glacier (France) taken over six consecutive years (2008–2013) allowed us to reconstruct daily ablation during the ablation period. Mean ablation rates ranged from 20 to 30 mm·day−1. Air temperature measurements showed that periods of low ablation during the summer were linked to cooler days and snowfall periods. Comparisons for three consecutive summers showed that the ablation rates obtained by summing calculated daily ablation were statistically similar to the rates recorded by ablation stakes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".