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Record W2093430157 · doi:10.3189/002214309790794823

A snow sensor experiment in Dronning Maud Land, Antarctica

2009· article· en· W2093430157 on OpenAlexaff
Hardy B. Granberg, P. Cliche, Olli-Pekka Mattila, Eija Kanto, Matti Leppäranta

Bibliographic record

VenueJournal of Glaciology · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversité de Sherbrooke
FundersAcademy of Finland
KeywordsKatabatic windSnowGeologyTransectAutomatic weather stationFirnPrecipitationIce shelfAtmospheric sciencesClimatologyPhysical geographyGeomorphologySea iceCryosphereOceanographyMeteorology

Abstract

fetched live from OpenAlex

Abstract In January 2000 nine snow sensors were deployed in Dronning Maud Land, Antarctica, along a 355 km transect from Kvitkuven near the shelf edge via the Finnish research station, Aboa, to the Amundsenisen plateau. The purpose was to test a sensor system for spatio-temporal variations in temperature across the snow–air interface and snow accumulation/ablation, which includes atmospheric net balance and migrating snow dunes. In the dry snow conditions, environmental static electricity interfered with data transfer; several sensors were disabled early, while the longest record reached 6 months. Along the main transect, the year 2000 mass balance ranged from 52 to 221 mm w.e., largely following spatial patterns seen by other researchers. The level increased toward the edge of the ice sheet; unloading of drifting snow as the slope flattens, rather than increased snowfall as previously thought, may be responsible for this. At the Högisen ice dome site the mass balance was 897 mm w.e., possibly due to unloading of wind-blown snow, as katabatic winds are locally forced uphill. This mechanism is important to maintain such topographic features along the Antarctic ice sheet margin. Major precipitation events occurred at 3–5 week intervals and much of the precipitation fell before mid-June. The daily signal in temperature disappeared after the autumn equinox, then the spectrum displayed a broad peak at synoptic frequencies. Potential temperature decreased towards the shelf edge, displaying a pattern consistent with strong inversions and suggesting that strong evaporative cooling is associated with the katabatic winds.

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 score0.012
Threshold uncertainty score0.693

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 head0.021
GPT teacher head0.255
Teacher spread0.234 · 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

Citations9
Published2009
Admission routes1
Has abstractyes

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