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Record W2770278720 · doi:10.5539/res.v9n4p177

Evaluation of Body Area Networks

2017· article· en· W2770278720 on OpenAlexvenueno aff
Sajad Ahmadian Naybin, Yosef Farhang

Bibliographic record

VenueReview of European Studies · 2017
Typearticle
Languageen
FieldEngineering
TopicWireless Body Area Networks
Canadian institutionsnot available
Fundersnot available
KeywordsWearable computerPower consumptionKey (lock)Consumption (sociology)Field (mathematics)Body area networkComputer scienceHuman healthTelecommunicationsWireless sensor networkPower (physics)Computer securitySociologyEmbedded systemComputer networkEnvironmental healthMedicineSocial science

Abstract

fetched live from OpenAlex

Body Area Network, due to recent advances in wearable sensors, intelligent surveillance with small size and low weight are made in low power consumption. Human physiological activities are constantly monitored by sensors. In this article, key controversies surrounding the field of BAN communications, including layers, and for example, the patient's health status and patterns of movement and etc.

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.

How this classification was reachedexpand

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.792
Threshold uncertainty score0.428

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 head0.089
GPT teacher head0.334
Teacher spread0.244 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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