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Record W7019728947

Impact of Extremely Low-Frequency Magnetic Fields on Human Postural Control

2016· article· en· W7019728947 on OpenAlexafffund

Bibliographic record

VenueScholarship@Western (Western University) · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicElectromagnetic Fields and Biological Effects
Canadian institutionsWestern University
FundersMitacsHydro-Québec
KeywordsWork (physics)Center of pressure (fluid mechanics)Postural instabilityHuman armInertiaMagnetic fieldExtremely low frequency
DOInot available

Abstract

fetched live from OpenAlex

The general public and workers can be exposed to high-levels of power-line frequency magnetic fields (MFs - up to 10 mT). Although such time-varying MFs have the potential to modulate human postural control, no existing studies have explored MF exposure levels that possibly trigger acute sway responses. This work evaluates time-varying MF exposure (up to 100 mT) in the extremely low frequency range (ELF – up to 300 Hz) and its effects on human postural control. Twenty-two healthy participants were each exposed to randomized, 5-second MF and electric stimulations (0, 50 and 100 mT and 1.5 mA respectively) given at different frequencies (20, 60, 90, 120, and 160 Hz). A force-plate collected participant Center Of Pressure (COP) displacement. Results revealed sway modulations resulting from electric stimulations but not from MF exposures. The mechanical stabilization induced by the inertia of the head-mounted exposure system might have masked acute sway responses.

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)0.000
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 score0.515
Threshold uncertainty score0.777

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 science0.0010.000
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 head0.044
GPT teacher head0.311
Teacher spread0.267 · 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 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

Citations0
Published2016
Admission routes2
Has abstractyes

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