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Record W2753209250 · doi:10.3189/2015jog14j227

Satellite observations show no net change in the percentage of supraglacial debris-covered area in northern Pakistan from 1977 to 2014

2015· article· en· W2753209250 on OpenAlexaff
Sam Herreid, Francesca Pellicciotti, Álvaro Ayala, Anna Chesnokova, Christian Kienholz, J. M. Shea, A. B. Shrestha

Bibliographic record

VenueJournal of Glaciology · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsÉcole de Technologie SupérieureUniversité du Québec à Montréal
FundersDepartment for International DevelopmentInternational Centre for Integrated Mountain Development
KeywordsDebrisGlacierGeologySurgePhysical geographySeries (stratigraphy)ClimatologyGeomorphologyGeographyOceanographyPaleontology

Abstract

fetched live from OpenAlex

Abstract Spatial evolution of supraglacial debris cover on mountain glaciers is a largely unmonitored and poorly understood phenomenon that directly affects glacier melt. Supraglacial debris cover for 93 glaciers in the Karakoram, northern Pakistan, was mapped from Landsat imagery acquired in 1977, 1998, 2009 and 2014. Surge-type glaciers occupy 41% of the study area and were considered separately. The time series of debris-covered surface area change shows a mean value of zero or near-zero change for both surging and non-surging glaciers. An increase in debris-covered area is often associated with negative regional mass balances. We extend this logic to suggest that the stable regional mass balances in the Karakoram explain the zero or near-zero change in debris-covered area. This coupling of trends combined with our 37 year time series of data suggests the Karakoram anomaly extends further back in time than previously known.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.291
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.075
GPT teacher head0.279
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; 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

Citations62
Published2015
Admission routes1
Has abstractyes

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