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Record W2091118550 · doi:10.1002/jnm.521

A novel approach to propagation prediction in confined and diffracting rough surfaces

2003· article· en· W2091118550 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

VenueInternational Journal of Numerical Modelling Electronic Networks Devices and Fields · 2003
Typearticle
Languageen
FieldEngineering
TopicMillimeter-Wave Propagation and Modeling
Canadian institutionsUniversité du QuébecUniversité du Québec en Abitibi-TémiscamingueUniversity of OttawaUniversité Laval
Fundersnot available
KeywordsMultipath propagationFadingSurface finishSurface roughnessComputer scienceDiffractionStatisticWirelessBendingCascadeAcousticsExtremely high frequencyElectronic engineeringEngineeringTelecommunicationsOpticsMaterials scienceStructural engineeringPhysicsMechanical engineeringMathematicsStatistics

Abstract

fetched live from OpenAlex

Abstract Modern wireless systems operating in the millimetre waves bands are now to be used in complex confined media such as mining environment. System designs require that multipath, fading and diffraction effects be accounted for in a suitable model. This paper presents a new propagation prediction method that can be used in mine corridors, buildings, underground roads, galleries with rough surfaces and others complex sub‐surface installations. A method named cascade impedance method (CIM) is used in combination with the segmental statistic method (SSM) in mine tunnels having considerable wall roughness and bending forms. Two (2D)‐ and three (3D)‐dimensional profiles of the radio waves are simulated and compared with available measurements at 2.45 and 18 GHz. Copyright © 2003 John Wiley & Sons, Ltd.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.899
Threshold uncertainty score0.388

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 head0.016
GPT teacher head0.224
Teacher spread0.208 · 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