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Record W2995062797 · doi:10.1002/mop.32202

Numerical modeling the propagation path of radio waves with atmospheric refractivity

2019· article· en· W2995062797 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

VenueMicrowave and Optical Technology Letters · 2019
Typearticle
Languageen
FieldEngineering
TopicRadio Wave Propagation Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsDepth soundingRadio propagationRefractive indexAtmospheric modelAtmospheric refractionAtmospheric pressureAtmospheric waveWave propagationRadio waveAtmospheric modelsMeteorologyAtmospheric soundingComputer simulationOptical pathRadio propagation modelRefractionAtmosphere (unit)Environmental scienceOpticsPhysicsGeologyComputer scienceMechanicsTelecommunicationsGravity wave

Abstract

fetched live from OpenAlex

Abstract The meteorological elements will affect the propagation of the radio wave. These meteorological elements can be reflected by the atmospheric refractive index, which is derived from the pressure, temperature, relative humidity, and vapor pressure. Using the atmospheric sounding data, a real atmospheric refractive index model for an identified area can be obtained. Combined with the refractive index model, the atmosphere can be divided into layered media with different refractive index, and a numerical model can be established to indicate the wave propagation path. The numerical solution results are verified by the analytical solution and other presented model. Due to its high accuracy and computational efficiency, the proposed numerical model can be used to quickly illustrate the physical path of radio wave atmospheric propagation, providing theoretical guidance for related applications.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.686
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.005
GPT teacher head0.186
Teacher spread0.181 · 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