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Record W1629093760

Experimentally assessed underground mines propagation model at high UHF frequencies

2010· article· en· W1629093760 on OpenAlexaff
M. Moutairou, G.Y. Delisle, Dominic Grenier

Bibliographic record

VenueEuropean Conference on Antennas and Propagation · 2010
Typearticle
Languageen
FieldEngineering
TopicMillimeter-Wave Propagation and Modeling
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsUltra high frequencyRay tracing (physics)Standard deviationMean squared errorRoot mean squareAntenna (radio)Power (physics)AcousticsComputer scienceEngineeringMathematicsOpticsStatisticsTelecommunicationsElectrical engineeringPhysics
DOInot available

Abstract

fetched live from OpenAlex

This paper shows that a ray-tracing model focused on reflected rays can be used for power prediction in an underground area. The model is calibrated and then validated in scenarios where the received power prediction efficiency is confirmed by experimental measurements recorded along three distinct routes in the same gallery with the transmitting antenna located at three different locations. Different positions of the transmitting antenna and their effects on the model are analysed and the efficiency of the model is shown using three indices such as mean error, standard deviation error or root mean squared error comparison. Some electromagnetic inputs parameters of the model are definitively analysed and their value are proposed to characterize propagation in the gallery area at 2.4 GHz.

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)
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 score0.771
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)0.0000.000

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 head0.037
GPT teacher head0.238
Teacher spread0.201 · 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 designBench or experimental
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

Citations2
Published2010
Admission routes1
Has abstractyes

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