MétaCan
Menu
Back to cohort

On the performance of CARISMA-Akademik Vernadsky station Schumann resonance monitoring

2023· article· en· W4385884868 on OpenAlexafffundabout
A. V. Koloskov, P. T. Jayachandran, Yu. M. Yampolski

Bibliographic record

VenueUkrainian Antarctic Journal · 2023
Typearticle
Languageen
FieldEngineering
TopicGeophysics and Sensor Technology
Canadian institutionsUniversity of New Brunswick
FundersScience and Technology Center in UkraineEuropean Office of Aerospace Research and DevelopmentMinistry of Education and Science of UkraineCanadian Space AgencyUniversity of Alberta
KeywordsSchumann resonancesEnvironmental sciencePhysicsGeophysics

Abstract

fetched live from OpenAlex

The main objective of this study is to evaluate the effectiveness of the CARISMA (Canadian Array for Realtime Investigations of Magnetic Activity) – Akademik Vernadsky station (65.25°S 64.25°W, Vernadsky) Extremely Low Frequency (ELF) induction magnetometer network as a planetary monitoring system for thunderstorm activity, with observation sites located in the Arctic and Antarctic regions, respectively. To achieve this, daily ELF records from Vernadsky and Fort Churchill (FCHU, 58.76°N 94.08°W) collected in January 2022 were processed and analyzed. For CARISMA, data from the FCHU site were used due to the better signal-to-noise ratio. The horizontal magnetic components of Schumann signals obtained at Vernadsky and FCHU underwent spectral and polarization processing. ELF transients were identified, and subsequent geolocation was performed as well. Both regular (quiet) thunderstorm activity periods and an unprecedented local amplification of lightning activity near the Hunga Tonga-Hunga Ha'apai volcano during its eruption on January 15, 2022, were studied. Throughout the quiet periods, ELF signal processing yielded similar characteristics of integral lightning activity derived from CARISMA and Vernadsky records, consistent with findings in the literature and previous investigations at the Vernadsky site. On the other hand, the analysis of Schumann spectra and ELF transients during the Tonga volcano eruption confirmed that most thunderstorms were concentrated within a relatively small area around the epicenter, validating the point source model for the global lightning center. This paper demonstrates that the CARISMA and Vernadsky magnetometer network is well-suited for establishing a global lightning activity monitoring andintense lightning geolocation system. Such a system can be employed to assess and study global temperature trends, monitor the growth of lightning activity in high latitudes, and detect terrestrial, atmospheric, and geospace disaster phenomena.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.069
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.218
Teacher spread0.202 · 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
Published2023
Admission routes3
Has abstractyes

Explore more

Same venueUkrainian Antarctic JournalSame topicGeophysics and Sensor TechnologyFrench-language works237,207