Updated gravity-derived bathymetry for the Thwaites, Crosson and Dotson ice shelves (2009-2022)
Bibliographic record
Abstract
This dataset is an estimate of sub ice shelf bathymetry beneath the Thwaites, Crosson and Dotson ice shelves. The output bathymetry is derived from a compilation of gravity data collected up to the end of the 2018/19 field season. The input gravity dataset includes airborne data from Operation Ice Bridge (OIB) and the NERC/NSF International Thwaites Glacier Collaboration (ITGC), and marine gravity from the R/V Nathaniel B. Palmer cruise NBP19-02. The recovered bathymetry was constrained by swath bathymetry in the open ocean, onshore airborne radio-echo depth sounding data and sub-shelf bathymetric observations from autonomous marine systems sent beneath the Dotson and Crosson Ice Shelves and seismic observations from the Crosson Ice Shelf surface. This bathymetric dataset supersedes the dataset of Jordan et al. 2020 (https://doi.org/10.5285/7803de8b-8a74-466b-888e-e8c737bf21ce ), as the new direct observations of sub-shelf bathymetry revealed the previously estimated depth of the basin beneath the Crosson and Dotson region to be ~400m too shallow. This inaccuracy is attributed to isostatic compensation of the deep basin, the mantle gravity effect of which was not considered in the original model. Included in the data release is the input free air gravity data, constraining bathymetry/sub-ice topography, isostatic gravity model, output gravity derived bathymetry including consideration of isostatic compensation which improves the fit to the new observed sub-shelf data and a final revised bathymetry dataset which incorporates the bathymetry from the gravity model with all bathymetric constraints. This work was funded by the Thwaites-Amundsen Regional Survey and Network Integrating Atmosphere-Ice-Ocean Processes (TARSAN) project, a component of the International Thwaites Glacier Collaboration (ITGC), from National Science Foundation (NSF: Grant 1929991) and Natural Environment Research Council (NERC: Grant NE/S006419/1)
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.006 |
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".