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Record W4391831873 · doi:10.5194/tc-18-711-2024

Brief communication: An ice-debris avalanche in the Nupchu Valley, Kanchenjunga Conservation Area, eastern Nepal

2024· article· en· W4391831873 on OpenAlexafffund
Alton C. Byers, Marcelo Somos‐Valenzuela, Dan H. Shugar, Daniel McGrath, Mohan Bahadur Chand, Ram Avtar

Bibliographic record

Venue˜The œcryosphere · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaAlberta InnovatesNational Aeronautics and Space AdministrationAgencia Nacional de Investigación y DesarrolloNuclear Safety and Security CommissionTribhuvan University
KeywordsDebrisPhysical geographyGeographyGeologyMeteorology

Abstract

fetched live from OpenAlex

Abstract. Beginning in December 2020, a series of small to medium, torrent-like pulses commenced upon a historic debris cone located within the Nupchu Valley, Kanchenjunga Conservation Area (KCA), Nepal. Sometime between 16 and 21 August 2022 a comparatively large ice-debris avalanche event occurred, covering an area of 0.6 km2 with a total estimated volume of order 106 m3. The area of the debris cone left by the August 2022 event increased the historic debris cone area by 0.2 km2 (total area 0.6 km2). Although no human or livestock deaths occurred, the increase in torrent-like pulses of debris upon this historic debris cone since 2020 exemplifies a style of mass movement that may become increasingly common as air temperatures rise in the region. Although the magnitude of this event was small compared to events like the 2021 Chamoli avalanche, the widespread distribution and frequency of comparable events present a substantial, and potentially increasing, hazard across High Mountain Asia.

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 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 score0.240
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.034
GPT teacher head0.243
Teacher spread0.209 · 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

Citations5
Published2024
Admission routes2
Has abstractyes

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