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Record W2089013035 · doi:10.3189/172756402781817554

Physical properties of the seasonal snow cover in Dronning Maud Land, East Antarctica

2002· article· en· W2089013035 on OpenAlexafffund
Eija Kärkäs, Hardy B. Granberg, Kimmo Kanto, Kai Rasmus, Chantale Lavoie, Matti Leppäranta

Bibliographic record

VenueAnnals of Glaciology · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversité de Sherbrooke
FundersCanadian Space AgencyAcademy of Finland
KeywordsGeologyKatabatic windSnowTransectFirnPlateau (mathematics)Snow lineIce shelfSea iceSnow fieldElevation (ballistics)PermafrostPhysical geographyOceanographyClimatologyCryosphereGeomorphologySnow coverGeography

Abstract

fetched live from OpenAlex

Abstract Snow stratigraphy was analyzed in the Maudheimvidda area of western Dronning Maud Land, East Antarctica, during austral summer 1999/2000 as a part of the Finnish Antarctic Research Programme (FINNARP). Measurements were made in shallow (1–2m) snow pits along a 350 km transect from the coast to the polar plateau, covering at least one annual cycle and an elevation range from sea level to about 2500 m. The aim of the study is to document spatial and temporal variations in snow-cover properties, with the further aim of relating these variations to environmental factors and to patterns observable by remote sensing. The measurements suggest five principal snow zones: (i) sea ice, (ii) the seaward edge zone of the ice shelf, (iii) the inner parts of the ice shelf, (iv) the snow cover above the grounding line and (v) the local topographic highs. Local topographic highs such as ice domes and ice rises differ from other snow environments: the snow is less densely packed, possibly an indication of locally reduced speed of the katabatic outflow. Fewer and thinner crusts on the topographic highs are consistent with RADARSAT backscatter variations.

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 score0.009
Threshold uncertainty score0.643

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)0.0010.000

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 head0.082
GPT teacher head0.250
Teacher spread0.168 · 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

Citations21
Published2002
Admission routes2
Has abstractyes

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