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Record W2138933528 · doi:10.1088/0031-9155/54/19/020

The discrepancy between human peripheral nerve chronaxie times as measured using magnetic and electric field stimuli: the relevance to MRI gradient coil safety

2009· article· en· W2138933528 on OpenAlexafffund
Bryan J. Recoskie, Timothy J. Scholl, Blaine A. Chronik

Bibliographic record

VenuePhysics in Medicine and Biology · 2009
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsWestern University
FundersNational Institute of Biomedical Imaging and BioengineeringNatural Sciences and Engineering Research Council of CanadaNational Institutes of HealthHort Innovation
KeywordsElectromagnetic coilNuclear magnetic resonancePeripheralPeripheral nerveRelevance (law)PhysicsMagnetic fieldNeurosciencePsychologyMedicineAnatomyQuantum mechanicsInternal medicine

Abstract

fetched live from OpenAlex

Peripheral nerve stimulation (PNS) resulting from electric fields induced from the rapidly changing magnetic fields of gradient coils is a concern in MRI. Nerves exposed to either electric fields or changing magnetic fields would be expected to display consistent threshold characteristics, motivating the direct application of electric field exposure criteria from the literature to guide the development of gradient magnetic field exposure criteria for MRI. The consistency of electric and magnetic field exposures was tested by comparing chronaxie times for electric and magnetic PNS curves for 22 healthy human subjects. Electric and magnetic stimulation thresholds were measured for exposure of the forearm using both surface electrodes and a figure-eight magnetic coil, respectively. The average chronaxie times for the electric and magnetic field conditions were 109 +/- 11 micros and 651 +/- 53 micros (+/-SE), respectively. We do not propose that these results call into question the basic mechanism, namely that rapidly switched gradient magnetic fields induce electric fields in human tissues, resulting in PNS. However, this result does motivate us to suggest that special care must be taken when using electric field exposure data from the literature to set gradient coil PNS safety standards in MRI.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.735
Threshold uncertainty score0.263

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 head0.112
GPT teacher head0.416
Teacher spread0.304 · 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 designTheoretical or conceptual
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

Citations28
Published2009
Admission routes2
Has abstractyes

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