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Record W1984291543 · doi:10.4236/jemaa.2013.54024

Minimum Attenuation of Physiologically-Patterned, 1 µTesla Magnetic Fields through Simulated Skull and Cerebral Space

2013· article· en· W1984291543 on OpenAlexaff
Michael A. Persinger, Kevin S. Saroka

Bibliographic record

VenueJournal of Electromagnetic Analysis and Application · 2013
Typearticle
Languageen
FieldMedicine
TopicAutomotive and Human Injury Biomechanics
Canadian institutionsLaurentian University
Fundersnot available
KeywordsAttenuationSkullMagnetic fieldAmplitudeIntensity (physics)Materials scienceHuman skullNuclear magnetic resonancePhysicsAcousticsOpticsAnatomyBiology

Abstract

fetched live from OpenAlex

To answer the queries concerning penetrability of ~1 μT, physiologically patterned, time-varying magnetic fields through the cranium, the proportions of attenuation through thicknesses and densities of ~3 times that of the human skull were measured directly. There was no reduction in the intensity of the magnetic field when two 2 cm thick dried pine boards (4.3 × 103 kg·m-3) were placed between the pairs of solenoids separated by the approximate width of the skull. Although volumes of water containing intracellular concentrations of ions did not attenuate the field intensity, placement of 290 cm2 of 2 mm sheets of duct metal reduced the amplitude by 25%. Spectra comparisons showed a clear congruence in profiles between direct measurement of the applied field and the original computer-generated pattern. These results indicate there is little validity to claims that weak, time-varying magnetic fields applied in this manner are eliminated or significantly attenuated by the human skull.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.010
GPT teacher head0.261
Teacher spread0.251 · 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 designSimulation or modeling
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

Citations9
Published2013
Admission routes1
Has abstractyes

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