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Record W4392119359 · doi:10.1139/cjes-2023-0074

Assessing the relative threats from Canadian volcanoes

2024· article· en· W4392119359 on OpenAlexafffundvenueabout
M C Kelman, Alexander M. Wilson

Bibliographic record

VenueCanadian Journal of Earth Sciences · 2024
Typearticle
Languageen
FieldComputer Science
TopicSeismology and Earthquake Studies
Canadian institutionsGeological Survey of Canada
FundersNatural Resources Canada
KeywordsVolcanoGeologySeismology

Abstract

fetched live from OpenAlex

We assessed 28 Canadian volcanoes in terms of their relative threats to people, aviation, and infrastructure. The methodology we used was developed by the United States Geological Survey for the 2005 National Volcano Early Warning System. Each volcano is scored on multiple hazard and exposure factors, producing an overall threat score. The scored volcanoes are assigned to five threat categories, ranging from Very Low to Very High. We developed a knowledge uncertainty score to provide additional information about assessed threat levels; this does not affect the threat scoring. Two Canadian volcanoes are in the Very High threat category (Mt. Garibaldi and Mt. Meager). Three Canadian volcanoes are in the High threat category (Mt. Cayley, Mt. Price, and Mt. Edziza) and one volcano is in the Moderate threat category (Mt. Silverthrone). We compare the ranked Canadian volcanoes to volcanoes in the USA and assess current levels of monitoring against internationally recognized monitoring strategies. We find that even one of the best-studied volcanoes in Canada (Mt. Meager) falls significantly short of the recommended monitoring level and is currently monitored at a level commensurate with a Very Low threat edifice. All other Canadian volcanoes are unmonitored (apart from falling within a regional seismic network). This threat ranking has been used to prioritize hazard and risk assessment targets and to help select monitoring activities that will most effectively address the undermonitoring of Canadian volcanoes.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.628
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.000
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 head0.046
GPT teacher head0.290
Teacher spread0.243 · 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.

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

Citations8
Published2024
Admission routes4
Has abstractyes

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