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Record W1519577012 · doi:10.1109/iembs.2003.1280934

Exploring current risks of mobile telephony in hospital and clinical environments

2004· article· en· W1519577012 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWireless Body Area Networks
Canadian institutionsCarleton UniversityUniversity of Ottawa
Fundersnot available
KeywordsPhoneEMIElectromagnetic interferenceCellular radioMobile phoneElectromagnetic compatibilityTelecommunicationsCellular networkBusinessMobile telephonyGovernment (linguistics)SignageTelephonyBase stationComputer scienceInternet privacyEngineeringMobile radioElectrical engineeringAdvertising

Abstract

fetched live from OpenAlex

A decade ago, anecdotal reports of cellular phones causing electromagnetic interference led government and health agencies to advocate the restriction of cellular phone in hospitals. Subsequently, many health facilities have instituted cellular phone restrictions enforced by signage and reprimanding staff. Despite these efforts, cellular phone activity maintains its momentum as the fastest growing source of electromagnetic interference (EMI) in hospitals. However, recent years have seen less EMI-related incidents. Perhaps it is time to update policies on cell phone usage in hospitals. We aim to discern the validity of the notion to lift cellular phones ban in North American and Canadian hospitals. We also present potential solutions for ensuring electromagnetic compatibility between cell phones and biomedical devices.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.733
Threshold uncertainty score0.386

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 head0.076
GPT teacher head0.299
Teacher spread0.222 · 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

Citations6
Published2004
Admission routes2
Has abstractyes

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