MétaCan
Menu
Back to cohort
Record W2107419358 · doi:10.1136/oem.2008.043380

Determinants of mobile phone output power in a multinational study: implications for exposure assessment

2009· article· en· W2107419358 on OpenAlexaff
Martine Vrijheid, Simon Mann, P. Di Vecchia, Joe Wiart, M. Taki, Lucia Ardoino, Bruce K. Armstrong, Anssi Auvinen, Daniel Bédard, Gabriele Berg‐Beckhoff, Jared A Brown, Angela Chetrit, Helle Collatz Christensen, E Combalot, Angus Cook, Isabelle Deltour, Maria Feychting, Graham G. Giles, Sarah Hepworth, Martine Hours, Ivano Iavarone, Christoffer Johansen, Daniel Krewski, Päivi Kurttio, Susanna Lagorio, Stefan Lönn, Mary L. McBride, L Montestrucq, Roger Parslow, Siegal Sadetzki, Joachim Schüz, Tore Tynes, Alistair Woodward, Elisabeth Cardis

Bibliographic record

VenueOccupational and Environmental Medicine · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicElectromagnetic Fields and Biological Effects
Canadian institutionsBC Cancer AgencyUniversity of Ottawa
FundersNational Institute for Health and Care Research
KeywordsMobile phoneGSMTelecommunicationsPhonePower (physics)Computer scienceStatisticsEconometricsMathematicsPhysics

Abstract

fetched live from OpenAlex

OBJECTIVES: The output power of a mobile phone is directly related to its radiofrequency (RF) electromagnetic field strength, and may theoretically vary substantially in different networks and phone use circumstances due to power control technologies. To improve indices of RF exposure for epidemiological studies, we assessed determinants of mobile phone output power in a multinational study. METHODS: More than 500 volunteers in 12 countries used Global System for Mobile communications software-modified phones (GSM SMPs) for approximately 1 month each. The SMPs recorded date, time, and duration of each call, and the frequency band and output power at fixed sampling intervals throughout each call. Questionnaires provided information on the typical circumstances of an individual's phone use. Linear regression models were used to analyse the influence of possible explanatory variables on the average output power and the percentage call time at maximum power for each call. RESULTS: Measurements of over 60,000 phone calls showed that the average output power was approximately 50% of the maximum, and that output power varied by a factor of up to 2 to 3 between study centres and network operators. Maximum power was used during a considerable proportion of call time (39% on average). Output power decreased with increasing call duration, but showed little variation in relation to reported frequency of use while in a moving vehicle or inside buildings. Higher output powers for rural compared with urban use of the SMP were observed principally in Sweden where the study covered very sparsely populated areas. CONCLUSIONS: Average power levels are substantially higher than the minimum levels theoretically achievable in GSM networks. Exposure indices could be improved by accounting for average power levels of different telecommunications systems. There appears to be little value in gathering information on circumstances of phone use other than use in very sparsely populated regions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.300
Teacher spread0.290 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations74
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueOccupational and Environmental MedicineSame topicElectromagnetic Fields and Biological EffectsFrench-language works237,207