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Record W2967952844 · doi:10.1002/9781119011866.ch19

ATMOSPHERIC PROPAGATION

2017· other· en· W2967952844 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

Venuenot available
Typeother
Languageen
FieldEngineering
TopicRadio Wave Propagation Studies
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsTerrainTroposphereMultipath propagationRadio propagationRemote sensingAtmospheric refractionGeologyAtmosphere (unit)RefractionSIGNAL (programming language)Computer scienceAtmospheric modelLine-of-sightGeodesyMeteorologyEnvironmental scienceGeographyTelecommunicationsAerospace engineeringPhysicsOpticsEngineering

Abstract

fetched live from OpenAlex

Reviewed here is the current state of knowledge with respect to each basic mechanism of sound propagation in the atmosphere and how each mechanism changes the spectral or temporal characteristics of the sound received at a distance from the source. Some of the basic processes affecting sound wave propagation which are present in any situation are discussed. They are geometrical spreading, molecular absorption, and turbulent scattering. In geometrical spreading, sound levels decrease with increasing distance from the source; there is no frequency dependence. In molecular absorption, sound energy is converted into heat as the sound wave propagates through the air; there is a strong dependence on frequency. In turbulent scattering, local variations in wind velocity and temperature induce fluctuations in phase and amplitude of the sound waves as they propagate through an inhomogeneous medium; there is a moderate dependence on frequency.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.001

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 head0.010
GPT teacher head0.219
Teacher spread0.209 · 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

Quick stats

Citations2
Published2017
Admission routes1
Has abstractyes

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