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Record W3152245248 · doi:10.1109/wsc.2006.323025

Wireless Network Simulation Extensions in SIDE/SMURPH

2006· article· en· W3152245248 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
Typearticle
Languageen
FieldComputer Science
TopicWireless Networks and Protocols
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsComputer scienceWireless networkInterference (communication)Stochastic geometry models of wireless networksWirelessWireless ad hoc networkChannel (broadcasting)Shadow mappingComputer networkRadio resource managementNetwork packetRadio propagationMobile radioTelecommunicationsArtificial intelligence

Abstract

fetched live from OpenAlex

We describe the most recent step in the evolution of SIDE/SMURPH and, specifically, a generic model of a wireless channel, which enables to use the package for accurately modeling wireless networks, especially ad-hoc networks consisting of a potentially large number of possibly mobile nodes. The generic nature of the channel model allows the user to introduce functions describing the propagation characteristics of the actual wireless medium, e.g., the impact of distance on signal level and interference, as well as the relationship between the signal-to-interference ratio and the probability of a successful packet reception. To illustrate the capabilities of the supported extensions, we review an example of a shadowing channel model

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 score0.965
Threshold uncertainty score0.394

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.259
Teacher spread0.245 · 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

Citations11
Published2006
Admission routes1
Has abstractyes

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