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Record W2103452519 · doi:10.5194/essd-5-319-2013

Juneau Icefield Mass Balance Program 1946–2011

2013· article· en· W2103452519 on OpenAlexaff
Mauri Pelto, Jeffrey L. Kavanaugh, Christopher McNeil

Bibliographic record

VenueEarth system science data · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Alberta
FundersNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsGlacierIce fieldGlacier mass balanceSnowAccumulation zonePhysical geographyGeologyTransectTidewater glacier cycleClimatologyGeomorphologyGeographyIce streamOceanographyCryosphereSea ice

Abstract

fetched live from OpenAlex

Abstract. The annual surface mass balance records of the Lemon Creek Glacier and Taku Glacier observed by the Juneau Icefield Research Program are the longest continuous glacier annual mass balance data sets in North America. Annual surface mass balance (Ba) measured on Taku Glacier averaged +0.40 m a−1 from 1946–1985, and −0.08 m a−1 from 1986–2011. The recent annual mass balance decline has resulted in the cessation of the long-term thickening of the glacier. Mean Ba on Lemon Creek Glacier has declined from −0.30 m a−1 for the 1953–1985 period to −0.60 m a−1 during the 1986–2011 period. The cumulative change in annual surface mass balance is −26.6 m water equivalent, a 29 m of ice thinning over the 55 yr. Snow-pit measurements spanning the accumulation zone, and probing transects above the transient snow line (TSL) on Taku Glacier, indicate a consistent surface mass balance gradient from year to year. Observations of the rate of TSL rise on Lemon Creek Glacier and Taku Glacier indicate a comparatively consistent migration rate of 3.8 to 4.1 m d−1. The relationship between TSL on Lemon Creek Glacier and Taku Glacier to other Juneau Icefield glaciers (Norris, Mendenhall, Herbert, and Eagle) is strong, with correlations exceeding 0.82 in all cases. doi:10.5065/D6NZ85N3

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.170
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.005

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 head0.042
GPT teacher head0.247
Teacher spread0.205 · 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; both teacher heads agree on what is shown here.

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

Citations38
Published2013
Admission routes1
Has abstractyes

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