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Updated gravity-derived bathymetry for the Thwaites, Crosson and Dotson ice shelves (2009-2022)

2025· dataset· en· W7114795719 on OpenAlexaff

Bibliographic record

VenueNERC Environmental Data Service · 2025
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of Manitoba
FundersNatural Environment Research CouncilNational Science Foundation
KeywordsBathymetryDepth soundingGlacierBathymetric chartIce shelfPost-glacial rebound

Abstract

fetched live from OpenAlex

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)

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Open science, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.009
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0060.009
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.019
GPT teacher head0.269
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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