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Record W2165575242 · doi:10.1109/sarnof.2008.4520075

Guaranteed Bandwidth Allocation and QoS support for Mobile Telemedicine Traffic

2008· article· en· W2165575242 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
FieldEngineering
TopicAdvanced Wireless Network Optimization
Canadian institutionsMcMaster University
Fundersnot available
KeywordsTelemedicineComputer scienceComputer networkTestbedBandwidth (computing)Quality of serviceWirelessWireless networkTelecommunicationsHealth care

Abstract

fetched live from OpenAlex

Cellular networks have been used in recent years as a testbed for the evaluation of the quality of low-bandwidth telemedicine traffic transmission. The correct and rapid transmission of telemedicine traffic is of utmost importance, therefore telemedicine video, audio and data cannot be treated similarly to regular traffic, but rather need to be offered absolute priority for transmitting over the wireless channel. On the other hand, if a portion of the bandwidth is dedicated to telemedicine traffic, this bandwidth will often be left unused as there is no constant need for transmission of telemedicine traffic in the network. Hence, in this paper we focus on the integration of telemedicine traffic with other traffic types in a cellular network and we introduce new scheduling ideas for the efficient transmission of telemedicine traffic.

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 score0.738
Threshold uncertainty score0.365

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 head0.008
GPT teacher head0.214
Teacher spread0.206 · 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

Citations15
Published2008
Admission routes1
Has abstractyes

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