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Record W2025799805 · doi:10.1002/hyp.5759

Geocryological processes linked to High Arctic proglacial stream suspended sediment dynamics: examples from Bylot Island, Nunavut, and Spitsbergen, Svalbard

2005· article· en· W2025799805 on OpenAlexaffabout
Tristram Irvine‐Fynn, Brian J. Moorman, Ian Willis, D. Sjogren, Andy Hodson, Paul Mumford, Fred Walter, Jessica Williams

Bibliographic record

VenueHydrological Processes · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsGlacierArcticGlacial periodFluvialSedimentGeologySTREAMSPhysical geographyGlacier terminusClimate changeGeomorphologyHydrology (agriculture)ClimatologyOceanographyStructural basinCryosphereIce streamGeographySea ice

Abstract

fetched live from OpenAlex

Abstract Recent research has identified differences in processes contributing to suspended sediment concentration (SSC) dynamics in proglacial streams between High Arctic and alpine catchments, but does not examine processes explicitly linked to the periglacial environment. Three glacierized basins were studied: Austre Brøggerbreen and Midre Lovénbreen, Svalbard (79°N, 12°E) and Glacier B28, unofficially named Stagnation Glacier, Bylot Island, Nunavut (73°N, 78°W). SSC variations were modelled from continuous turbidity, discharge and meteorological data throughout the summer months. Three statistical tools were utilized: principal component analysis, change‐point analysis and multivariate regression. These are shown to be effective in identifying subperiods of distinctive geocryological and glaciofluvial characteristics. Multivariate regression for the subseasons included autoregressive integrated moving‐average modelling, and showed that SSC variations were related not only to discharge variability, but also to fluctuations in energy fluxes. The results are interpreted in terms of spatio‐temporal changes in sediment mobilization and supply associated with changes in the relative importance of fluvial, glacial and periglacial processes. This evidence supports the notion of important linkages between glacial, fluvial and periglacial systems, but exemplifies distinct variability between High Arctic glaciers. Copyright © 2005 John Wiley & Sons, Ltd.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.022
GPT teacher head0.226
Teacher spread0.204 · 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.

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

Citations28
Published2005
Admission routes2
Has abstractyes

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