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Record W2151922086 · doi:10.1109/jsac.2009.090508

Bridging between ieee 802.15.4 and IEEE 802.11b networks for multiparameter healthcare sensing

2009· article· en· W2151922086 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 Journal on Selected Areas in Communications · 2009
Typearticle
Languageen
FieldComputer Science
TopicWireless Networks and Protocols
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsComputer scienceComputer networkIEEE 802.15Bridging (networking)Network packetIEEE 802IEEE 802.11Wireless sensor networkWireless networkWirelessTelecommunicationsQuality of service

Abstract

fetched live from OpenAlex

In this paper we consider the interconnection of an IEEE 802.15.4 body area network (BAN) in which nodes sense physiological variables such as electrocardiography (EKG), electroencephalography (EEG), pulse oximeter data, blood pressure and cardiac output, with an IEEE 802.11b room/ward WLAN. We model the operation of this two-tier network assuming that 802.15.4 BAN operates in CSMA-CA mode and that the BAN coordinator acts as the bridge which conveys BAN packets to the 802.11b access point. We analyze the two-hop network delay and discuss the mutual interaction of different data streams as well as impact of the number of bridges on packet delay.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.939
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0000.002
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 head0.061
GPT teacher head0.342
Teacher spread0.281 · 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