Dynamics and mass balance of Taylor Glacier, Antarctica: 1. Geometry and surface velocities
Bibliographic record
Abstract
Taylor Glacier, Antarctica, exemplifies a little‐studied type of outlet glacier, one that flows slowly through a region of rugged topography and dry climate. This glacier, in addition, connects the East Antarctic Ice Sheet with the McMurdo Dry Valleys, a region much studied for geomorphology, paleoclimate, and ecology. Here we report extensive new measurements of surface velocities, ice thicknesses, and surface elevations, acquired with InSAR, GPS, and GPR. The latter two were used to construct elevation models of the glacier's surface and bed. Ice velocities in 2002–2004 closely matched those in 2000 and the mid‐1970s, indicating negligible interannual variations of flow. Comparing velocities with bed elevations shows that, along much of the glacier, flow concentrates in a narrow axis of relatively fast flowing ice that overlies a bedrock trough. The flow of the glacier over major undulations in its bed can be regarded as a “cascade”; it speeds up over bedrock highs and through valley narrows and slows down over deep basins and in wide spots. This pattern is an expected consequence of mass conservation for a glacier near steady state. Neither theory nor data from this Taylor Glacier study support the alternative view, recently proposed, that an outlet glacier of this type trickles slowly over bedrock highs and flows fastest over deep basins.
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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 | 0.001 |
| 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".