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Record W2113415054 · doi:10.1657/aaar0013-102

Decadal-Scale Variations in Glacier Area Changes Across the Southern Patagonian Icefield Since the 1970s

2015· article· en· W2113415054 on OpenAlexafffund
Adrienne White, Luke Copland

Bibliographic record

VenueArctic Antarctic and Alpine Research · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Ottawa
FundersNatural Resources CanadaCanadian Natural Resources Limited
KeywordsIce fieldGlacierGlacier mass balanceAdvanced Spaceborne Thermal Emission and Reflection RadiometerPrecipitationGeologyClimatologyElevation (ballistics)Physical geographyDigital elevation modelGeographyGeomorphologyMeteorologyRemote sensing

Abstract

fetched live from OpenAlex

Abstract A combination of Landsat and ASTER satellite scenes are used to quantify changes in the areal extent of glaciers in 130 basins across the Southern Patagonian Icefield (SPI). There was extensive net overall loss, with a reduction in ice area of 542 km2 (∼4% of the SPI) between the late 1970s and 2008/2010. For glaciers measured within individual periods, average losses occurred at a rate of 3.24% decade-1 between 1976/1979 and 1984/1986, 2.04% decade-1 between 1984/1986 and 2000/2002, and 2.24% decade-1 between 2000/2002 and 2008/2010. This indicates sustained losses, but no evidence for a recent acceleration. Since the 1980s, glaciers located in the northwest part of the SPI experienced the highest mean annual loss rates at 2.9% decade-1. Mean glacier elevation provides the only significant topographic control on glacier changes for all measurement periods, and glacier losses are consistent with recent warming and changes in precipitation observed for this region.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score0.947

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 studies0.0010.000
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 head0.096
GPT teacher head0.322
Teacher spread0.226 · 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

Citations16
Published2015
Admission routes2
Has abstractyes

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