MétaCan
Menu
← Back to cohort
Record W4283160199 · doi:10.5194/icg2022-26

Snow avalanches as the main geomorphic active process on hillslopes in Nunavik, Canada

2022· preprint· en· W4283160199 on OpenAlexaffabout
Armelle Decaulne, Najat Bhiry, Jérémy Grenier, Funatsu Beatriz

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsUniversité LavalCenter for Northern Studies
Fundersnot available
KeywordsSnowDebrisWater equivalentSpring (device)Hydrology (agriculture)GeologyAtmospheric sciencesPhysical geographyGeomorphologyGeographyPhysicsOceanographyGeotechnical engineering

Abstract

fetched live from OpenAlex

In Nunavik, northern Quebec, Canada, ongoing climate change disturbs the nival regime. The study of deposits on talus underlines the predominance of snow avalanches as the main contributor to present-day slope development. In Tasiapik valley, close to the village of Umiujaq (56°32'35"N, 76°27'43"W), several automatic time-lapse cameras are operating year-round since 2017 along with VDTSILA weather station since 2012. The set of cameras enables monitoring target sections of the slope. The recorded snow avalanches correspond to slab and loose snow avalanches; many are triggered by the collapse of the ridgeline snow-cornices. The most active snow-avalanche season corresponds to late spring (June), when wet snow avalanches occurred after rain-on-snow events and rapid temperature rise, being then in contact with the regolith, therefore responsible of debris transfer downslope. However, the longest runout distance snow avalanches occur during the winter time, in April, after sudden temperatures changes or heavy snowfall. However, by comparing the snow-avalanche activity from other slopes (lake Wiyâshâkimî, 56°16'43"N, 74°27'48"O and Kangiqsualujjuaq, 58°41'33"N, 65°57'32"O) equipped with the same monitoring system, great variations appear in snowfall amount, snowdrift accumulation and triggering factors, sketching the role of continentality and latitude. In addition, in the vicinity of newly established villages due to the forced settlement of indigenous populations, snow avalanches represent a worrying hazard.

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 score0.014
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.007
GPT teacher head0.222
Teacher spread0.214 · 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

Citations0
Published2022
Admission routes2
Has abstractyes

Explore more

Same topicLandslides and related hazards→French-language works237,207→