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Record W7098254020

A Wildfire Risk Management System – An Evolution of the

2014· article· en· W7098254020 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsnot available
Fundersnot available
KeywordsDisturbance (geology)Risk managementRisk assessmentNatural (archaeology)Rating systemWildland–urban interfaceManagement systemWater safety
DOInot available

Abstract

fetched live from OpenAlex

In 2002 the Greater Vancouver Water District began a collaborative project to develop a Wildfire Risk Management System for three municipal watersheds (Capilano, Coquitlam and Seymour) that provide drinking water to the Greater Vancouver Region of Southwestern British Columbia. Wildfire is a natural disturbance agent in these heavily forested coastal watersheds that has the potential to negatively impact water quality, public safety and property, and air quality. Historically these areas have been exposed to low frequency (300-600 years), high severity stand replacement fires that have the potential to significantly alter physical and chemical water properties. Although the probability of large wildfires within these watersheds is considered low, the consequences associated with a large wildfire could be devastating to both the watersheds and the adjacent interface communities. The Wildfire Threat Rating System has been developed for a number of applications and scales throughout British Columbia over the past six years. In previous applications, all fire related factors (fire risk, suppression capability, fire behavior and values at risk) were rated equally without consideration of traditional risk management theory. The revised system

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.837
Threshold uncertainty score0.244

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 head0.008
GPT teacher head0.172
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 designTheoretical or conceptual
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
Published2014
Admission routes1
Has abstractyes

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