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Record W4403180467 · doi:10.1029/2024gl110456

Tracking the Filling, Outburst Flood and Resulting Subglacial Water Channel From a Large Canadian Arctic Subglacial Lake

2024· article· en· W4403180467 on OpenAlexafffundabout
Laurence Gray, Benoît Lauzon, Luke Copland, Wesley Van Wychen, Christine F. Dow, William Kochtitzky, Karen E. Alley

Bibliographic record

VenueGeophysical Research Letters · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of ManitobaUniversity of WaterlooUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsPolar Knowledge Canada
KeywordsGeologyFlood mythArcticChannel (broadcasting)Tracking (education)GeomorphologyThe arcticOceanographyGeography

Abstract

fetched live from OpenAlex

Abstract We use digital elevation models (DEMs) and ICESat‐2 data to study the filling and outflow from a large subglacial lake under Manson Icefield in the Canadian Arctic. When full, the lake is ∼17 × 3 km with an area of 52 km2. Early in 2021 the ice surface over the center of the lake sank by >140 m implying a subglacial outburst flood of ∼4 km3. Rapid outflow occurred over ∼30 days at an average rate of ∼1,500 m3s−1 resulting in the formation of a single ∼15 km subglacial outflow path detectable from post‐outflow surface depression. The shape of the surface depression, 600–800 m wide by 2–4 m deep, reflects the shape of the subglacial channel prior to closure. Downstream ice movement appears unaffected by the outflow. After outflow ends the surface depression persisted over weeks, apparently dependent on the difference between water and overburden pressures.

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 score0.046
Threshold uncertainty score0.093

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 science0.0000.000
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 head0.042
GPT teacher head0.271
Teacher spread0.229 · 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

Citations4
Published2024
Admission routes3
Has abstractyes

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