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Record W1974378850 · doi:10.5047/eps.2011.07.020

Monitoring of the ionosphere TEC variations during the 17th August 1999 Izmit earthquake using GPS data

2011· article· en· W1974378850 on OpenAlexaff
Uǧur Doǧan, Semih Ergintav, S. Skone, Niyazi Arslan, Deniz Öz Demir

Bibliographic record

VenueEarth Planets and Space · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEarthquake Detection and Analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsTECIonosphereTotal electron contentGlobal Positioning SystemGeologyGeodesySeismologyGeophysicsComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

In this paper, we aim to determine a snapshot of previously unstudied ionospheric variations which were recorded in a two-week interval before and after a large earthquake of M 7.6 occurred on 17 August, 1999, in the Marmara region of Turkey. We detected ionospheric perturbations before the earthquake occurred using Global Positioning System (GPS) data received from the Marmara Continuous GPS Network (MAGNET). Pre-seismic ionospheric total electron content (TEC) anomalies were observed three days before the earthquake at sets of stations near the earthquake location, while post-seismic traveling ionospheric disturbances could not be detected. The ionospheric variability had a negative sign with an enhancement of about 8–10 TECU (1 TECU = 10 16 electrons/m 2 ) relative to the non-distributed state of the ionosphere. The results show that this method will be a useful addition to the already-available continuous monitoring techniques in the region.

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)0.000
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.042
GPT teacher head0.217
Teacher spread0.175 · 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

Citations26
Published2011
Admission routes1
Has abstractyes

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