Bibliographic record
Abstract
Glacier surges have been shown to cluster non-randomly in many mountain regions of the world but the underlying processes remain little understood.This manuscript presents an innovative approach to the study of the climatic forcing of glacier surges in Donjek glacier, Canada, with a combination of ice core, meteorological, remote sensing and GPR data, giving an strong insight on the glacier surging main forcings.The work compiles existing data from a series of previous works of this well studied glacier, and builds on with significant new evidence.The results are convincing and conclusions seem particularly strong because they apply to seven surge cycles.Discussion is valuable and focusses on the interpretation and some limitations of the results.I have some comments regarding a small part of the methods, some of the writing and C1Printer-friendly version Discussion paperLine 395.This is a bit simplistic since ELA depends on both temperature and precipitation.Line 402.Verify if the unit is m.e.instead of m 2 .Line 405.After enlarging consider including 5 yr markes on the x axis of Fig 7.
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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 | 0.005 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.466 | 0.277 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".