MétaCan
Menu
Back to cohort
Record W1558526850 · doi:10.1002/2015gl064508

Observed platelet ice distributions in Antarctic sea ice: An index for ocean‐ice shelf heat flux

2015· article· en· W1558526850 on OpenAlexaff
Patricia J. Langhorne, Kenneth Hughes, A. J. Gough, Inga J. Smith, Michael Williams, Natalie Robinson, Craig Stevens, Wolfgang Rack, Daniel Price, Greg H. Leonard, Andrew R. Mahoney, Christian Haas, T. G. Haskell

Bibliographic record

VenueGeophysical Research Letters · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsYork University
FundersMinistry of Science and Innovation, New ZealandFoundation for Research, Science and TechnologyNational Institute of Water and Atmospheric Research
KeywordsIce shelfSea iceAntarctic sea iceGeologyCryosphereSea ice thicknessArctic ice packDrift iceOceanographyIcebergFast iceClimatologyIce sheet

Abstract

fetched live from OpenAlex

Abstract Antarctic sea ice that has been affected by supercooled Ice Shelf Water (ISW) has a unique crystallographic structure and is called platelet ice. In this paper we synthesize platelet ice observations to construct a continent‐wide map of the winter presence of ISW at the ocean surface. The observations demonstrate that, in some regions of coastal Antarctica, supercooled ISW drives a negative oceanic heat flux of −30 Wm −2 that persists for several months during winter, significantly affecting sea ice thickness. In other regions, particularly where the thinning of ice shelves is believed to be greatest, platelet ice is not observed. Our new data set includes the longest ice‐ocean record for Antarctica, which dates back to 1902 near the McMurdo Ice Shelf. These historical data indicate that, over the past 100 years, any change in the volume of very cold surface outflow from this ice shelf is less than the uncertainties in the measurements.

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)0.001
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 score0.120
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.101
GPT teacher head0.318
Teacher spread0.217 · 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

Citations111
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueGeophysical Research LettersSame topicCryospheric studies and observationsFrench-language works237,207