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Record W2096715583 · doi:10.1109/iembs.2001.1017466

Detecting skin burns induced by surface electrodes

2005· article· en· W2096715583 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicOcular and Laser Science Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsElectrodeMaterials scienceComputer scienceBiomedical engineeringEngineeringChemistry

Abstract

fetched live from OpenAlex

The origin of electrical burns under gel-type surface electrodes is a controversial topic that is not well understood. To investigate the phenomenon, we have developed an excised porcine skin+gel model. In the present paper, we describe methods to detect these burns in the skin+gel model in an effort to understand the genesis of these burns. Burns were induced by severe electrical stimulation and changes in the impedance spectra and current density measured. We found that the changes in impedance spectrum were characterized by a significant drop in the low frequency (<1 kHz) impedance magnitude and the formation of welts in the skin. Low frequency current density imaging (LFCDI) revealed regions of high current density beneath the electrode before burns were induced suggesting the possibility of predicting the locations where welts from burns will form and the importance of current density and local tissue impedance in the formation of these burns.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.590

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)0.0010.000

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 head0.023
GPT teacher head0.329
Teacher spread0.307 · 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

Quick stats

Citations8
Published2005
Admission routes1
Has abstractyes

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