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Computer simulation of commercial conductive gels and their application to increase the safety of electrochemotherapy treatment

2019· article· en· W2975631214 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

VenueMedical Engineering & Physics · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Inactivation Methods
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsElectrochemotherapyBleomycinElectrical conductorMaterials scienceElectroporationBiomedical engineeringElectric fieldHomogeneity (statistics)Composite materialSurgeryMedicineComputer scienceChemistryChemotherapy

Abstract

fetched live from OpenAlex

Electrochemotherapy (ECT) exploits the phenomenon of electroporation, which is the increase of cell permeability through the application of an electrical field. This technique is applied in medical centers in Europe and in veterinary clinics in Europe, Brazil, and Argentina. ECT treatment requires a minimum electric field and anti-cancer drugs (e.g., bleomycin). Irregularly shaped tumors may induce ECT treatment failure because of irregular electric field distribution. Conductive gels have been suggested as a means to increase the homogeneity of the electrical field distribution. The aim of this work was to evaluate if commercial conductive gels could increase the safety of ECT. A veterinary case study of ECT in a dog provided the tumor dimensions for the numerical model. Electrode displacement and commercial conductive gels were simulated to determine if they improved ECT treatments. We conclude that a commercial gel having a conductivity of 0.2 S/m when used in combination with effective treatment planning may improve the outcome of electrochemotherapy procedures.

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 score0.473
Threshold uncertainty score0.204

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 head0.006
GPT teacher head0.261
Teacher spread0.255 · 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