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Record W2047594680 · doi:10.3189/172756404781814168

Superimposed-ice formation in summer on Ross Sea pack-ice floes

2004· article· en· W2047594680 on OpenAlexaff
Toshiyuki Κawamura, Martin O. Jeffries, Jean‐Louis Tison, H. Roy Krouse

Bibliographic record

VenueAnnals of Glaciology · 2004
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversity of Calgary
FundersServices Fédéraux des Affaires Scientifiques, Techniques et CulturellesFonds De La Recherche Scientifique - FNRSMinistry of Education, Culture, Sports, Science and TechnologyNational Science Foundation
KeywordsGeologySlushSea iceAntarctic sea iceArctic ice packPancake iceIce divideSea ice thicknessIce shelfFast iceDrift iceIce streamCryosphereGeomorphologyOceanography

Abstract

fetched live from OpenAlex

Abstract Austral summer sea-ice processes were investigated in January 1999 during a cruise of the R.V. Nathaniel B. Palmer in the central and eastern Ross Sea, Antarctica. The crystal texture, 18 O/ 16 O ratios, density and salinity of ice cores and of ice blocks ‘perched’ on slush at the ice surface were studied. The perched ice blocks had a distinctive polygonal granular (PG) crystal texture and very negative isotope signature that were also characteristic of layers at the top of first-year floes and of layers ‘buried’ below the surface in multi-year floes. The PG ice is superimposed ice that results from melting in the snow cover and refreezing at the slush surface and directly on top of ice floes. If PG ice is buried after the ice surface floods and the resultant slush freezes, then snow ice forms above the PG ice. The contribution of superimposed ice to floe surface mass balance and some implications with respect to weather and climate are discussed.

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 score0.054
Threshold uncertainty score0.372

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.045
GPT teacher head0.285
Teacher spread0.240 · 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

Citations29
Published2004
Admission routes1
Has abstractyes

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