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Record W2148306782 · doi:10.1657/1938-4246-42.1.9

An Analysis of Past and Future Changes in the Ice Cover of Two High-Arctic Lakes Based on Synthetic Aperture Radar (SAR) and Landsat Imagery

2010· article· en· W2148306782 on OpenAlexaboutno aff
Timothy L Cook, Raymond S. Bradley

Bibliographic record

VenueArctic Antarctic and Alpine Research · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
FundersU.S. Geological Survey
KeywordsArcticCryosphereArctic ice packPhysical geographyClimatologyPermafrostSea iceSynthetic aperture radarGeologyMelt pondLatitudeClimate changeAntarctic sea iceSatellite imageryEnvironmental scienceOceanographyRemote sensingGeography

Abstract

fetched live from OpenAlex

Abstract Space-borne remotely sensed data can provide valuable insight into cryospheric processes in remote high-latitude regions for which direct observations are limited. In this study we use synthetic aperture radar (SAR) and Landsat imagery to evaluate recent changes in the ice cover of Upper and Lower Murray Lakes (81°20′N, 69°30′W) on Ellesmere Island, Nunavut, Canada. These data highlight changes in ice conditions that have occurred over the past decade and provide a means for assessing the likely impacts of rising temperatures on future lake-ice conditions. Under current (1997–2007) climatic conditions the Murray Lakes average several weeks of ice-free conditions in August and early September, although in some years a partial ice cover persists throughout the year. The observed relationship between summer temperature and ice melt at Upper and Lower Murray Lakes suggests that recent warming in the High Arctic has forced the lakes near a threshold from a state characterized by perennial ice cover to the current state that includes seasonal melting of lake ice. Projected future warming will significantly increase the duration of ice free conditions on Upper and Lower Murray Lakes, with ice-out predicted to occur 13.5 ± 4.0 and 17.6 ± 5.6 days earlier, respectively, for every 1 °C increase in mean June–July temperature.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.294
Teacher spread0.268 · 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.

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

Citations24
Published2010
Admission routes1
Has abstractyes

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