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Record W7006596295

Volumetric change of Klinaklini and Tiedemann Glaciers, Southern Coast Mountains, British Columbia, Canada

2008· article· en· W7006596295 on OpenAlexaboutno aff

Bibliographic record

VenueWestern CEDAR (Western Washington University) · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
Fundersnot available
KeywordsGlacierThinningDebrisGlacier mass balanceDigital elevation modelClimate changeAerial photography
DOInot available

Abstract

fetched live from OpenAlex

Glaciers of the Southern Coast Mountains are an important source of freshwater in the province, but few studies detail their volumetric change. We utilized digital elevation models (DEMs) from aerial photography (1965, 1985) and from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery (2000, 2006) to calculate thickness and volumetric changes in the ablation zones of Klinaklini and Tiedemann glaciers. The ablation area of Klinaklini Glacier thinned by an average of - 150 ± 17 m and lost -13.9 ± 1.7 km3 during the period 1965-2006 while Tiedemann Glacier thinned -49 ± 20 m and lost -1.1 ± 0.5 km3 over the same interval. Klinaklini Glacier experienced maximum rates of thinning and volumetric change during the period 2000-2006, while the highest rates of thinning and ice loss for Tiedemann Glacier occurred 1985-2000, which corresponds to one of the warmest periods of the 20th century. Differences in size and debris cover may explain the variable response of the glaciers to climate change. Work is in progress to extend the analysis further back using 1949 aerial photography.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.015
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.176
Teacher spread0.151 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2008
Admission routes1
Has abstractyes

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