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Record W2328158675 · doi:10.3189/2013jog12j192

The effects of El Niño and La Niña on snow and avalanche patterns in British Columbia, Canada, and central Chile

2013· article· en· W2328158675 on OpenAlexafffundabout
D. M. McClung

Bibliographic record

VenueJournal of Glaciology · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsSnowPrecipitationAltitude (triangle)GeologyClimatologyDeposition (geology)Climate changePhysical geographyEnvironmental scienceAtmospheric sciencesMeteorologyGeomorphologyGeographyOceanography

Abstract

fetched live from OpenAlex

Abstract El Niño and La Niña affect global climate and atmospheric circulation to determine winter temperature and precipitation patterns. Both winter temperatures and the associated precipitation patterns have effects on mountain snow deposition and snow avalanche occurrences. Approximately 25 000 slab avalanches from 30 winters were analyzed in relation to snowfall patterns contrasted for El Niño and La Niña winters for two avalanche areas with different snow climates in British Columbia (BC), Canada. La Niña winters were shown to produce more snow, more avalanches and a higher percentage of dry avalanches than wet avalanches. The data and analysis show that the avalanche patterns depend on the altitude and snow climate. Analysis of snowfall and accident data from the Andes of Chile suggests behavior opposite to BC. El Niño winters in central Chile produced the most snow and, by inference, the most avalanches. This paper is the first to show the links of El Niño and La Niña to snow avalanche activity.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.212
Threshold uncertainty score0.229

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)0.0000.000

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 head0.003
GPT teacher head0.167
Teacher spread0.164 · 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.

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

Citations33
Published2013
Admission routes3
Has abstractyes

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