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Record W4391224152 · doi:10.62252/nss.2024.1005

What is the primary culprit that causes the "Doomsday Glacier" in Antarctica?

2024· article· en· W4391224152 on OpenAlexaff
Jijun Zhang

Bibliographic record

VenueNaturalis scientias. · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsCustom Security Industries (Canada)
FundersUniversität BremenUniversity of Oregon
KeywordsGeologyGlacierCryosphereEarth scienceGeothermal gradientVolcanoOceanographyClimatologyGeophysicsSea iceGeomorphologyPaleontology

Abstract

fetched live from OpenAlex

Antarctica, situated in the southernmost part of the earth is surrounded by the Southern Ocean. It has an extremely important role in tuning global climate, both because of its geographic location, and its giant ice mass, that comprises ~90% of the world's ice. In the past decades, the Thwaites Glacier in the Amundsen Sea of West Antarctica is undergoing the fastest recession in the region. The ice loss in Thwaites Glacier is currently responsible for roughly four percent of the global sea-level rise, which has been attributed to climate change and ocean warming. Due to the continuous collapsing and melting of Thwaites Glacier and the severe threat to humans, scientists gave it a terrifying name "Doomsday Glacier". With increasingly geological and geophysical studies conducted in West Antarctica, geothermal heat flux has been discovered to play a vital role in icesheet retreating. The rapidly retreating Thwaites and Pope glaciers are underlain by areas of largely elevated geothermal heat flow, which relates to the tectonic and magmatic history of the West Antarctic Rift System in this region, suggesting that this area is coupled to the dynamics of the underlying lithosphere. The collapsing and melting of the West Antarctic glaciers are without doubt a realistic and complex issue. From the current geological surveys, the heat flux of the crust of West Antarctica appears to be accelerating, coupled with frequent earthquakes and volcanoes. Geothermal features such as hot water lakes, thermal rivers, and giant ice caves beneath the glaciers have been continuously discovered. Therefore, it is reasonable to speculate that geothermal effects play a significant role in modifying the vast ice masses, causing glacier sliding, cracking, collapsing, and ultimately melting, and create conditions for a warming climate to melt West Antarctic glaciers. Many studies also suggest that warm ocean water is intruding beneath the glaciers across the grounding line, leading to melting of glacier bottom, which has been generally considered to be associated with human-emitted greenhouse gases, but it is thought here not to be a primary factor for glacier melting, but most likely a secondary factor. It is believed that primary and secondary factors, Milankovitch orbits, black body radiation, solar activities, human activities, and other factors are all interconnected to form a feedback loop between the glacier base and the ocean, or even a positive feedback loop, which further accelerates the collapsing and melting of the west Antarctic glaciers

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.003

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 head0.026
GPT teacher head0.249
Teacher spread0.223 · 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 source (direct Gemma or distilled Codex), 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
Published2024
Admission routes1
Has abstractyes

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