Mass balance of East Antarctic glaciers and ice shelves from satellite data
Bibliographic record
Abstract
Abstract The velocity and mass discharge of nine major East Antarctic glaciers not draining into the Ross or Filchner–Ronne Ice Shelves is investigated using interferometric synthetic aperture radar (InSAR) data from the European Remote-sensing Satellite 1and 2 (ERS-1/2) andRADARSAT-1. The glaciers are: David,Ninnis, Mertz, Totten, Scott, Denman, Lambert, Shirase and Stancomb-Wills. InSAR is used to locate their grounding line with precision. Ice velocity is measured with either InSAR or a speckle-tracking technique. Ice thickness is deduced from prior-determined ice-shelf elevation assuming hydrostatic equilibrium. Mass fluxes are calculated both at the grounding line and at a flux gate located downstream. The grounding-line flux is compared to a mass input calculated from snow accumulation to deduce the glacier mass balance. The calculation is repeated at the flux gate downstream of the grounding line to estimate the average bottom melt rate of the ice shelf under steady-state conditions. The main results are: (1) Grounding lines are found several tens of km upstream of prior-identified positions, not because of a recent ice-sheet retreat but because of the inadequacy of prior-determined grounding-line positions. (2) No gross imbalance between outflow and inflow is detected on the nine glaciers being investigated, with an uncertainty of 10–20%. Prior-determined, largely positive mass imbalances were due to an incorrect localization of the grounding line. (3) High rates of bottom melting (24±7 mice a–1) are inferred near grounding zones, where ice reaches the deepest draft. A few glaciers exhibit lower bottom melt rates (4±7 mice a–1). Bottom melting, however, appears to be a major source of mass loss on Antarctic ice shelves.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".