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Record W203509084

Mountain Weather Forecasting in BC for Avalanche Safety

2006· article· en· W203509084 on OpenAlexaboutno aff
Melinda M. Brugman

Bibliographic record

VenueProceedings of the 2006 International Snow Science Workshop, Telluride, Colorado · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsnot available
Fundersnot available
KeywordsMeteorologyProbabilistic logicStormEnvironmental scienceWeather forecastingClimatologyComputer scienceGeographyArtificial intelligenceGeology
DOInot available

Abstract

fetched live from OpenAlex

A special weather bulletin is produced during the winter season at the Pacific Storm Prediction Centre (PSPC) in Vancouver to support avalanche forecasting efforts in British Columbia. This paper will present a history of this Canadian Avalanche Centre (CAC) bulletin and trace its usage. Verifications are examined. Major forecast busts and hits are examined for several situations related hazardous avalanche conditions in BC – most notably strong southwesterly flows and stalled frontal bands. Weather variables which are most important for improved avalanche safety are identified for each region and suggestions made for how probabilistic ensemble forecasting may improve weather forecasts. The value of direct communication with a trained forecaster is shown through the time-honored traditions of the technical synopses (short term and extended), confidence statements and daily phone briefings. Future improvements will depend on how well we can build upon existing expertise while better communicating new advancements to avalanche professionals and those whose safety depends on accurate mountain weather forecasts.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.215
Threshold uncertainty score0.433

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0130.002

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 head0.009
GPT teacher head0.225
Teacher spread0.216 · 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
Published2006
Admission routes1
Has abstractyes

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Same venueProceedings of the 2006 International Snow Science Workshop, Telluride, ColoradoSame topicLandslides and related hazardsFrench-language works237,207