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Record W4405516367 · doi:10.1186/s40677-024-00304-6

Glacial lakes inventory and susceptibility assessment in the Alsek River Basin, Yukon, Canada

2024· article· en· W4405516367 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueGeoenvironmental Disasters · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
FundersUniverzita Karlova v Praze
KeywordsGlacierGlacial periodGlacial lakeMorainePhysical geographyClimate changeGeologyNatural hazardStructural basinHydrology (agriculture)GeomorphologyOceanographyGeography

Abstract

fetched live from OpenAlex

Abstract Background This study investigates glacial lake outburst floods (GLOFs) within the Alsek River Basin, Yukon, Canada, a region experiencing accelerated glacier retreat due to climate change. The formation and expansion of glacial lakes pose significant hazards to geomorphological and ecological systems, even in the absence of human infrastructure. Despite extensive research in other glaciated regions such as the Himalayas and Andes, the Canadian Cordillera remains understudied. This research aims to inventory glacial lakes and assess their susceptibility to GLOFs using remote sensing techniques and two distinct methodologies. Results A total of 590 glacial lakes were identified, with 57 in direct or indirect contact with glaciers, warranting a detailed susceptibility assessment. The study applied the glacier-focused methodology of Wang et al. (Mt Res Dev 31(2):122 (2011). https://doi.org/10.1659/mrd-journal-d-10-00059.1 ) and the lakespecific dynamics approach of Khadka et al. (Front Earth Sci 8(January):1–16 (2021). https://doi.org/10.3389/feart.2020.601288 ). Key findings include: High-Hazard Lakes: Lakes 22, 23, 133, 134, and 275 were consistently identified as high-hazard due to factors such as large glacier inputs, steep moraine dams, and rapid expansion rates. GLOF Events: Four GLOF events were confirmed between 2017 and 2019, with the most significant reducing Lake 21's area by over 80%. Comparative Analysis: The integration of both methodologies provided a comprehensive understanding, revealing complementary insights into glacier-driven and lake-specific GLOF triggers. Conclusion The results underscore the critical role of glacier retreat and lake dynamics in driving GLOF hazards in the Alsek River Basin. The study highlights the importance of combining multiple assessment methodologies for robust hazard evaluation. Given the dynamic nature of glacial lakes and ongoing climate change, continuous monitoring and proactive hazard management strategies are essential to mitigate potential geomorphological and ecological impacts. This research contributes to the broader understanding of GLOFs in North America and underscores the need for similar assessments in other understudied glaciated regions.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.554
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.010
GPT teacher head0.203
Teacher spread0.193 · 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