MétaCan
Menu
Back to cohort
Record W2331386032 · doi:10.1109/tpds.2015.2447528

Analysis of CSMA/CA Mechanism of IEEE 802.15.6 under Non-Saturation Regime

2015· article· en· W2331386032 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

VenueIEEE Transactions on Parallel and Distributed Systems · 2015
Typearticle
Languageen
FieldEngineering
TopicWireless Body Area Networks
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsComputer scienceComputer networkBody area networkWirelessBandwidth (computing)IEEE 802.11e-2005Software deploymentIEEE 802.15Channel (broadcasting)Wireless networkWireless lanWireless sensor networkTelecommunicationsWi-Fi array

Abstract

fetched live from OpenAlex

We have developed an analytical model for a non-saturated IEEE 802.15.6 wireless body area network (WBAN) operating under an error-prone channel. The most suitable vehicle for improving network performance was found to be the choice of access phase lengths based on traffic loads for different user priorities (UPs). It was also found that the deployment of exclusive access phase (EAP) is not necessary in a typical WBAN; in fact, short exclusive and random access phases (EAP and RAP, respectively) lead to inefficient use of available bandwidth. We have also found that four user priorities (out of the eight available) typically suffice to achieve even the most stringent requirements for WBAN performance.

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 score0.929
Threshold uncertainty score0.842

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.019
GPT teacher head0.222
Teacher spread0.203 · 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