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Record W4206967547 · doi:10.32920/16828243.v1

Investigating The Effects Of Pulsed Radiofrequency Therapy In The Blocking Of Action Potentials In Nerves

2021· preprint· en· W4206967547 on OpenAlexaff
Aryan Safakish

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMagnetic and Electromagnetic Effects
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPulsed radiofrequencyNeurophysiologyBlocking (statistics)Sensory systemBiomedical engineeringAction potentialMedicineMaterials scienceAnesthesiaNeuroscienceElectrophysiologyInternal medicineComputer sciencePain reliefBiology

Abstract

fetched live from OpenAlex

Radiofrequency (RF) currents (pulsed or continuous mode) are used as a treatment modality for chronic pain management. This is achieved by blocking sensory nerves’ ability to propagate pain signals. In this thesis, it was proposed that pulsed RF (PRF) therapy can block action potential propagation, and that when used in clinical settings, deliver thermal doses below the threshold for thermal damage to nerves. A neurophysiology system with stimulating and reading electrodes was used to study earthworm nerves before and after PRF therapy. It was shown that 60% of earthworms in the high-voltage-group treated with bipolar PRF experienced a block in action potential propagation. Computer simulations of the electrical field and heating patterns were created, experimentally validated, and after determining a threshold thermal dose for nerve damage, it was shown that for C6 medial branch nerve PRF therapy the temperature at the nerve was not high enough to cause thermal damage.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.013
GPT teacher head0.268
Teacher spread0.254 · 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 designBench or experimental
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
Published2021
Admission routes1
Has abstractyes

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