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Record W4251421637 · doi:10.4095/301265

Space Weather - Telluric Activity Zones

2010· report· en· W4251421637 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typereport
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsnot available
Fundersnot available
KeywordsSpace weatherSpace (punctuation)MeteorologyEnvironmental scienceGeologyGeographyClimatologyComputer science

Abstract

fetched live from OpenAlex

The magnetic field of the Earth is influenced by the electromagnetic environment of the solar system. The disturbed interplanetary environment changes the conditions of the natural electromagnetic environment of our planet and affects normal operation of space and ground technological infrastructures, such as power grids and pipelines. The geomagnetically induced currents that directly affect vulnerable infrastructure are driven by the geoelectric (telluric) field. Therefore, the most important task in space weather hazard mapping is to identify the areas with different levels of telluric activity. On the map, telluric activity is defined as the annual percentage of the time when variations in the activity is above the normal level of 20 milliVolts per kilometre. Elevated telluric activity occurrs for a quarter of the year in the auroral zone, whereas it varies from 15 percent (4.5 times per month) down to just a few percent (1 occurrence per two months) in the Prairies. It is interesting to note that most of the big cities in Canada, and therefore much of the infrastructure, are in the least tellurically active zone (less than 10 percent).

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.058
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0180.004

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 head0.027
GPT teacher head0.261
Teacher spread0.234 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2010
Admission routes1
Has abstractyes

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