Bibliographic record
Abstract
The prediction of crustal motions and gravity change driven by glacial isostatic adjustment (GIA) in Antarctica is critically dependent on the reconstruction of the configuration and thickness of the ice sheet during the Late Pleistocene and Holocene. The collection and analysis of field data to improve the reconstruction has occurred at an accelerated pace during the past decade. At the same time, space-based imaging and altimetry, combined with on-ice velocity measurements using Global Positioning System (GPS) geodesy, has provided better assessments of the present-day mass balance of the Antarctic ice sheet. Present-day mass change appears to be dominated by deglaciation that is, in large part, a continuation of late-Holocene evolution. Here a new ice load model is constructed, based on a synthesis of the current constraints on past ice history and present-day mass balance. The load is used to predict GIA crustal motion and geoid change. Compared to existing glacioisostatic models, the new ice history model is significantly improved in four aspects: (i) the timing of volume losses in the region ranging from the Ross Sea sector to the Antarctic Peninsula, (ii) the maximum ice heights in parts of the Ellsworth and Transantarctic Mountains, (iii) maximum grounding line position in Pine Island Bay, the Antarctic Peninsula, and in the Ross Sea, (iv) incorporation of present-day net mass balance estimates. The predicted present-day GIA uplift rates peak at 14–18 mm yr −1 and geoid rates peak at 4–5 mm yr −1 for two contrasting viscosity models. If the asthenosphere underlying West Antarctica has a low viscosity then the predictions could change substantially due to the extreme sensitivity to recent (past two millennia) ice mass variability. Future observations of crustal motion and gravity change will substantially improve the understanding of sub-Antarctic lithospheric and mantle rheology.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".