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Record W1640593231 · doi:10.1029/2010ja016248

Daytime midlatitude<i>D</i>region parameters at solar minimum from short-path VLF phase and amplitude

2011· article· en· W1640593231 on OpenAlexaboutno aff
Neil R. Thomson, Mark A. Clilverd, Craig J. Rodger

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsnot available
FundersNatural Environment Research CouncilSight Research UK
KeywordsIonosphereEarth's magnetic fieldAmplitudeGeomagnetic latitudeDaytimeMiddle latitudesGeologyF regionPhysicsLatitudeGeophysicsGeodesyAtmospheric sciencesMagnetic fieldOptics

Abstract

fetched live from OpenAlex

[1] Observed phases and amplitudes of VLF radio signals propagating on a short (∼360 km) path are used to find improved parameters for the lowest edge of the (D region of the) Earth's ionosphere at a geomagnetic latitude of ∼53.5° in midsummer near solar minimum. The phases, relative to GPS 1 s pulses, and the amplitudes were measured both near (∼110 km from) the transmitter, where the direct ground wave is very dominant, and at distances of ∼360 km near where the ionospherically reflected waves form a (modal) minimum with the (direct) ground wave. The signals came from the 24.0 kHz transmitter, NAA, on the coast of Maine near the U.S.-Canada border, propagating ∼360 km E-NE, mainly over the sea, to Saint John and Prince Edward Island. The bottom edge of the midday, midsummer, ionosphere at ∼53.5° geomagnetic latitude was thus found to be well modeled by H′ = 71.8 ± 0.6 km and β = 0.335 ± 0.025 km−1 where H′ and β are Wait's traditional height and sharpness parameters used by the U.S. Navy in their Earth-ionosphere VLF radio waveguide programs. The variation of β with latitude is also estimated with the aid of interpolation using measured galactic cosmic ray fluxes.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.549
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.047
GPT teacher head0.313
Teacher spread0.266 · 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.

Study designOther design
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

Citations57
Published2011
Admission routes1
Has abstractyes

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