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Record W4377862304 · doi:10.1139/as-2023-0001

Patterns and mechanisms of repeat drainages of glacier-dammed Dań Zhùr (Donjek) Lake, Yukon

2023· article· en· W4377862304 on OpenAlexafffundvenueabout
Moya Painter, Luke Copland, Christine F. Dow, William Kochtitzky, Dorota Medrzycka

Bibliographic record

VenueArctic Science · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of WaterlooUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsParks CanadaUniversity of WaterlooAssociation of Canadian Universities for Northern StudiesUniversity of Ottawa
KeywordsSurgeGlacierGeologySubaerialCanyonGlacier terminusGlacier mass balanceTidewater glacier cycleGlacier ice accumulationIce tongueShelf iceCirque glacierPhysical geographyOceanographyGeomorphologyHydrology (agriculture)Ice streamCryosphereIce calvingSea icePaleontologyGeography

Abstract

fetched live from OpenAlex

Dań Zhùr (Donjek) Glacier is a surge-type glacier that undergoes cyclical periods of rapid advance over ∼1–2 years, followed by retreat for ∼10 years. Since the 1990s, the advances have caused the formation of ice-dammed Dań Zhùr Lake, which has filled and drained in summers following a surge event. Here, we report how these drainages initially occur through a subglacial channel under the glacier terminus, which then typically closes the following winter, enabling another lake to form and drain the next summer. However, our remote sensing and field observations indicate that after several drainage events, a subaerial ice canyon is formed through the glacier terminus, which prevents another lake from forming until after the glacier surges again. We predict that the next surge of Dań Zhùr Glacier will occur around the mid-2020s, causing the formation of a larger Dań Zhùr Lake during the following quiescent phase because, despite periodic advances, a long-term trend of glacier recession is exposing a larger basin for the lake to form in. However, each subsequent surge is causing less terminus advance than the previous one, until ultimately the surges will be insufficient to dam Dań Zhùr Chù’ (Donjek River), and lakes will cease to form.

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 score0.889
Threshold uncertainty score0.222

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 studies0.0010.001
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 head0.026
GPT teacher head0.236
Teacher spread0.211 · 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

Citations2
Published2023
Admission routes4
Has abstractyes

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