Monitoring the physical processes driving the mass loss of Tapado Glacier, Dry Andes of Chile
Bibliographic record
Abstract
Abstract We summarise 15 years of field and remote monitoring of Tapado Glacier in north-central Chile (30° S). Observations include meteorological records, direct mass balance measurements, uncrewed aerial vehicle surveys and tri-stereo satellite imagery for deriving high-resolution elevation changes. Frequent droughts and a significant warming trend of 0.29°C decade−1 since 1974 have caused a decrease in glacier surface albedo and an accelerated loss of glacier area and mass, particularly since the onset of the Chilean Megadrought in 2010, associated here with a 43% winter precipitation deficit. Geodetic estimates indicate increasingly more negative mass balance, varying from slightly negative before 2000 to −0.18 ± 0.35 m w.e. a−1 in 2000–12, −0.44 ± 0.11 m w.e. a−1 in 2012–20 and −0.75 ± 0.12 m w.e. a−1 after 2020. Glacier mass loss is associated with several morphological changes, such as increased penitente height, a larger total surface area of ice cliffs and supraglacial ponds over the debris-covered section and more frequent falls of snow and ice from marginal ice surrounding a steep area of exposed bedrock. Tapado Glacier exemplifies how glacier mass loss is driven by various processes, requiring multiple monitoring techniques, and highlights the accelerated changes of the Andes cryosphere.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".