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Record W2163313455 · doi:10.3189/172756507782202829

Tributary glacier surges: an exceptional concentration at Panmah Glacier, Karakoram Himalaya

2007· article· en· W2163313455 on OpenAlexafffund
Kenneth Hewitt

Bibliographic record

VenueJournal of Glaciology · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsWilfrid Laurier University
FundersInternational Development Research CentreWilfrid Laurier University
KeywordsSurgeGlacierTributaryGeologyCirque glacierGlacier mass balanceGlacier terminusSnowTidewater glacier cycleGlacier ice accumulationClimate changePhysical geographyGlacier morphologyGlacial periodClimatologyIce streamGeomorphologyCryosphereOceanographySea iceIce calvingGeography

Abstract

fetched live from OpenAlex

Abstract Four tributaries of Panmah Glacier have surged in less than a decade, three in quick succession between 2001 and 2005. Since 1985, 13 surges have been recorded in the Karakoram Himalaya, more than in any comparable period since the 1850s. Ten were tributary surges. In these ten a full run-out of surge ice is prevented, but extended post-surge episodes affect the tributary and main glacier. The sudden concentration of events at Panmah Glacier is without precedent and at odds with known surge intervals for the glaciers. Interpretations must consider the response of thermally complex glaciers, at exceptionally high altitudes and of high relief, to changes in a distinctive regional climate. It is suggested that high-altitude warming affecting snow and glacier thermal regimes, or bringing intense, short-term melting episodes, may be more significant than mass-balance change.

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)0.000
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 score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.025
GPT teacher head0.258
Teacher spread0.233 · 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

Citations283
Published2007
Admission routes2
Has abstractyes

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