Glacial Isostatic Adjustment in a region of complex Earth structure: The case of WAIS
Bibliographic record
Abstract
In this thesis, we consider surface loading effects associated with our dynamic cryosphere. Glacial Isostatic Adjustment (GIA) models have been used to constrain the extent of past ice sheets and viscoelastic Earth structure, and to correct geodetic and geological observations for ice age effects. These models, however, often only consider depth-dependent variations in Earth viscosity and lithospheric structure. Seismic, geological, and geodetic evidence indicates the Antarctic Ice Sheet is underlain by complex, high amplitude variability in 3-D viscoelastic structure. In contrast with West Antarctica’s low viscosity mantle, Canada, the location of the former Laurentide Ice Sheet, is underlain by a thick craton and mantle viscosities higher than the global average. GIA modeling with 3-D mantle structure requires greater model specificity and fidelity, but will also provide a deeper understanding of the past and future evolution of the cryosphere. Our investigation is motivated by two questions: How does 3-D Earth structure impact observations of GIA-induced deformation, and how will 3-D Earth structure affect predictions of sea-level change? We compute gravitationally self-consistent uplift, gravity, and sea-level changes and show that 3-D Earth structure will have significant effects on sea-level changes associated with West Antarctic Ice Sheet melt during interglacial periods. Further, we show that Antarctica’s viscoelastic structure will impact geodetic observables even for timescales when the Earth is commonly treated as a purely elastic body. We demonstrate how the bias in crustal deformation induced by this 3-D structure will impact standard methods to use GPS observations to infer viscoelastic structure in West Antarctica. Finally, we use sea-level modeling to estimate the emergence of an island from Canada’s waters in order to corroborate an Indigenous people’s land claim.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".