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Record W2944659599 · doi:10.1029/2019gl082457

Effects of an Explosive Polar Cyclone Crossing the Antarctic Marginal Ice Zone

2019· article· en· W2944659599 on OpenAlexfundno aff
Marcello Vichi, Clare Eayrs, Alberto Alberello, Anriëtte Bekker, Luke G. Bennetts, David M. Holland, Ehlke de Jong, Warren Joubert, Keith MacHutchon, Gabriele Messori, Jhon F. Mojica, Miguel Onorato, Clinton Saunders, Sebastian Skatulla, Alessandro Toffoli

Bibliographic record

VenueGeophysical Research Letters · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
FundersSwedish Foundation for International Cooperation in Research and Higher EducationDepartment of Science and Technology, Republic of South AfricaNational Science Foundation, United Arab EmiratesNational Research FoundationYork UniversityEuropean Organization for the Exploitation of Meteorological SatellitesVetenskapsrådetACE FoundationSvenska Forskningsrådet FormasNew York University Abu Dhabi
KeywordsExtratropical cycloneSea iceGeologyCyclone (programming language)ClimatologyDrift iceAntarctic sea iceArctic ice packMiddle latitudes

Abstract

fetched live from OpenAlex

Abstract Antarctic sea ice shows a large degree of regional variability, which is partly driven by severe weather events. Here we bring a new perspective on synoptic sea ice changes by presenting the first in situ observations of an explosive extratropical cyclone crossing the winter Antarctic marginal ice zone (MIZ) in the South Atlantic. This is complemented by the analysis of subsequent cyclones and highlights the rapid variations that ice‐landing cyclones cause on sea ice: Midlatitude warm oceanic air is advected onto the ice, and storm waves generated close to the ice edge contribute to the maintenance of an unconsolidated surface through which waves propagate far into the ice. MIZ features may thus extend further poleward in the Southern Ocean than currently estimated. A concentration‐based MIZ definition is inadequate, since it fails to describe a sea ice configuration which is deeply rearranged by synoptic weather.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.617
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.013
GPT teacher head0.263
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; 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

Citations132
Published2019
Admission routes1
Has abstractyes

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