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Record W202327814

Cooperation between the Nordic countries and Japan in advanced ice sheet and glacier modeling

2011· article· en· W202327814 on OpenAlexaboutno aff
Ralf Greve, Thomas Zwinger

Bibliographic record

VenueHokkaido University Collection of Scholarly and Academic Papers (Hokkaido University) · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
Fundersnot available
KeywordsGlacierIce sheetGeologyGlacier morphologyFact sheetGreenland ice sheetCryospherePhysical geographyClimatologyIce streamGeographyGeomorphologySea iceComputer science
DOInot available

Abstract

fetched live from OpenAlex

An ice sheet is a grounded ice body with an area greater than 50,000 km2. The only current ice sheets on Earth are in Antarctica and Greenland, while during the maximum of the last glacial period about 21,000 years ago the Laurentide ice sheet covered much of Canada and North America, the Fennoscandian ice sheet covered northern Europe and the Patagonian ice sheet covered southern South America. Smaller grounded ice bodies, depending on their size, are termed ice caps or glaciers, their number exceed 100,000, and they exist on all continents. Ice sheets, ice caps and glaciers feature gravity-driven free surface flow (“glacial flow”), controlled by pressure, internal stresses, temperature and basal friction. Since the late 1970s, numerical modeling has become established as an important technique for the understanding of ice dynamics. Ice sheet, ice cap and glacier models are particularly relevant for predicting their possible response to climate change and consequent sea level rise, and thus a number of such models have been developed over the years. Recent observations actually suggest that ice dynamics could play a crucial role in predicting future sea level rise under global warming conditions. Despite this great relevance, ice sheet and glacier modeling is still heavily underrepresented within the domestic and international climatology communities, compared to the large efforts made into atmosphere and ocean research. The need for further research into the matter was even explicitly stated in the Fourth Assessment Report (AR4) of the United Nations Intergovernmental Panel on Climate Change (IPCC): “Dynamical processes related to ice flow not included in current models but suggested by recent observations could increase the vulnerability of the ice sheets to warming, increasing future sea level rise. Understanding of these processes is limited and there is no consensus on their magnitude.” (IPCC 2007). In this talk, recent and ongoing collaborative efforts between the Nordic countries (in particular Finland, Norway, Sweden and Denmark) and Japan on ice sheet, ice cap and glacier modeling will be reviewed. This includes the application of models of various complexities to problems of past, present and future states and changes (including response to global warming) of the Antarctic and Greenland ice sheets, the Austfonna ice cap on Svalbard and a crater glacier in Kamchatka.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.875

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.027
GPT teacher head0.186
Teacher spread0.158 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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
Published2011
Admission routes1
Has abstractyes

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