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Record W3172191503 · doi:10.1126/science.abh4455

A massive rock and ice avalanche caused the 2021 disaster at Chamoli, Indian Himalaya

2021· article· en· W3172191503 on OpenAlexafffund
Dan H. Shugar, Mylène Jacquemart, David Shean, Shashank Bhushan, Kavita Upadhyay, Ashim Sattar, Wolfgang Schwanghart, Sara K. McBride, Maximillian Van Wyk de Vries, Martin Mergili, Adam Emmer, César Deschamps‐Berger, Morgan McDonnell, Rakesh Bhambri, Simon Allen, Étienne Berthier, Jonathan L. Carrivick, John J. Clague, М.Д. Докукин, Stuart Dunning, Holger Frey, Simon Gascoin, Umesh K. Haritashya, Christian Huggel, Andreas Kääb, Jeffrey S. Kargel, Jeffrey L. Kavanaugh, Pascal Lacroix, David N. Petley, Summer Rupper, Mohd Farooq Azam, Simon J. Cook, A. P. Dimri, Martin Eriksson, Daniel Farinotti, Joel Fiddes, Kaushal Raj Gnyawali, Stephan Harrison, M. Jha, Michèle Koppes, Amit Kumar, Silvan Leinss, Ulfat Majeed, Suraj Mal, Arnab Muhuri, Jeannette Noetzli, F. Paul, Irfan Rashid, Kalachand Sain, Jakob Steiner, Felipe Ugalde, C. Scott Watson, Matthew Westoby

Bibliographic record

VenueScience · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaUniversity of AlbertaSimon Fraser UniversityUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaNatural Environment Research CouncilSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungDepartment of Science and Technology, Ministry of Science and Technology, IndiaSight Research UKNational Aeronautics and Space AdministrationEuropean Space AgencyCooperative Institute for Research in Environmental SciencesDirektion für Entwicklung und ZusammenarbeitInternational Centre for Integrated Mountain DevelopmentCentre national d'études spatiales
KeywordsGeologyPhysical geographyGeography

Abstract

fetched live from OpenAlex

cubic meters of rock and glacier ice collapsed from the steep north face of Ronti Peak. The rock and ice avalanche rapidly transformed into an extraordinarily large and mobile debris flow that transported boulders greater than 20 meters in diameter and scoured the valley walls up to 220 meters above the valley floor. The intersection of the hazard cascade with downvalley infrastructure resulted in a disaster, which highlights key questions about adequate monitoring and sustainable development in the Himalaya as well as other remote, high-mountain environments.

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 score0.050
Threshold uncertainty score0.100

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 studies0.0040.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.005
GPT teacher head0.207
Teacher spread0.201 · 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

Citations810
Published2021
Admission routes2
Has abstractyes

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