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Record W2068607280 · doi:10.1541/jae.34.69

An attempt to correlate first mode Schumann resonance intensity with ground surface temperature at low latitudes

2014· article· en· W2068607280 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Atmospheric Electricity · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEarthquake Detection and Analysis
Canadian institutionsChrysler (Canada)
FundersDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsLatitudeSchumann resonancesIntensity (physics)Low latitudeLinear regressionMode (computer interface)MagnetometerResonance (particle physics)Correlation coefficientAtmospheric sciencesMeteorologyGeologyEnvironmental sciencePhysicsGeodesyMathematicsOpticsStatisticsGeophysicsMagnetic fieldAtomic physicsComputer science

Abstract

fetched live from OpenAlex

Employing a system of 3-component search coil magnetometer installed in a remote area in the out skirt of Agra (Geographic lat.27.2°N, long.78°E), India, Schumann resonance (SR) observations have been in progress since 01 April, 2007. In this paper we analyze the first mode intensity data for a period of one year between 01 March, 2011 and 29 February, 2012 and correlate with ground surface temperature (GST) for low latitude region between ± 30° latitude.The GST data are taken from the website: http://www.tutiempo.net. Our results show that the variation curves of the two sets of data match satisfactorily with cross-correlation coefficient of 0.522 which is consistent with earlier workers for low latitude region. We also carry out linear regression analysis and regression equation is utilized to verify the calculated and measured GST which are found to be matching satisfactorily also.

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.

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 score0.163
Threshold uncertainty score0.705

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 studies0.0000.000
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 head0.004
GPT teacher head0.194
Teacher spread0.190 · 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