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Record W4392587771 · doi:10.5194/egusphere-egu24-2746

YeMiGO: Data Processing and Analysis of Underground Superconducting Gravity Data in South Korea

2024· preprint· en· W4392587771 on OpenAlexaff
J. J. Oh, Mohammad Javad Dehghan, Ik Woo, Hwansun Kim, Edwin J. Son, SeungMi You, Jeong Woo Kim

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsData processingGeologySeismologyDatabaseComputer science

Abstract

fetched live from OpenAlex

We present the status of the Yemi micro-gravity observatory (YeMiGO), including the installation, operation, and initial analysis of the gravity data. In October 2022, we installed GWR Instruments Inc,’s iGrav (serial #001) superconducting gravimeter (SG) at Yemi underground laboratory (YemiLab) in South Korea. YemiLab is located approximately 1,008 and 118 meters below the Earth's surface and mean sea level, respectively. The noise characteristics were assessed using one month of raw data collected in September 2023 and compared to those of other seismometer stations. The results show the noise level at the SG station, especially in the seismic band, is significantly low and proves the stability of the Lab.  The research findings also indicate that blasting during mining operations at a distance between ~700 and ~900 meters (please confirm this) from the SG impacted the dewar and barometer pressures as well as the tilt balance data. However, no discernible effects were observed in the raw SG data, leading to the hypothesis that the SG tilt system was able to compensate for the resulting vibrations. After 6 months of continuous data recording from 16th November 2022 to 18th May 2023, a calibration factor of -92.17 μGal∙V-1 was estimated using tidal analysis. In November 2023, a new calibration factor of -94.15 μGal∙V-1 was estimated using parallel measurements with FG5-231 provided by the Ministry of Interior, R.O.C. (Taiwan). Having accounted for various environmental effects, including Earth tide, atmospheric pressure, groundwater level, and polar motion, during the initial six months of data, the residual gravity was obtained. Spectral analysis revealed several unidentified residual gravity power spectrum density frequencies, necessitating further investigation. Co-seismic gravity changes resulting from four earthquakes in May 2023 with different magnitudes and within various distances from the SG station were examined. The M6.2 earthquake that occurred 765 km away was linked to the most notable co-seismic gravity alteration, which recorded a value of 0.561 μGal. The mentioned changes decreased gradually and faded away entirely within half an hour after the SG's first arrival.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.275
Threshold uncertainty score0.963

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.001
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 head0.150
GPT teacher head0.306
Teacher spread0.156 · 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 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
Published2024
Admission routes1
Has abstractyes

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