Uncertainties of Glacial Isostatic Adjustment Model Predictions in North America Associated With 3D Structure
Bibliographic record
Abstract
Abstract We quantify GIA prediction uncertainties of 250 1D and 3D glacial isostatic adjustment (GIA) models through comparisons with deglacial relative sea‐level (RSL) data from North America and rate of vertical land motion ( ) and gravity rate of change ( ) from GNSS and GRACE data, respectively. Spatially, the size of the RSL uncertainties varies across North America with the largest from Hudson Bay and near previous ice margins along the northern Atlantic and Pacific coasts, which suggests 3D viscosity structure in the lower mantle and laterally varying lithospheric thickness. Temporally, RSL uncertainties decrease from the Last Glacial Maximum to present except for west of Hudson Bay and the northeastern Pacific coast. The uncertainties of both these regions increase from 30 to 45 m between 15 and 11 ka BP, which may be due to the rapid decrease of surface loading at that time. Present‐day and uncertainties are largest in southwestern Hudson Bay with magnitudes of 2.4 mm/year and 0.4 μ Gal/year, mainly due to the 3D viscosity structure in the lower mantle.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".