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A stochastic model for transepidermal drug delivery

2009· article· en· W2058078837 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSkin Research and Technology · 2009
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicAdvancements in Transdermal Drug Delivery
Canadian institutionsUniversity of Manitoba
FundersManitoba Health Research Council
KeywordsTransepidermal water lossStratum corneumComputer scienceDrug deliveryDrugBiomedical engineeringDermatologyMedicineMedical physicsPharmacologyMaterials scienceNanotechnologyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Topical drug application has been widely used to manage skin diseases as well as to treat a variety of local and systemic disorders. To evaluate the efficiency of transepidermal drug delivery, an efficient model is needed to study the process of percutaneous transport. MODEL DESCRIPTION: A stochastic model based on Monte Carlo methods and Cellular Automata is presented in this work to study the molecular transport through the stratum corneum of the human skin, which is a typical process in transepidermal drug delivery. METHODS: To validate the model, an in vitro experiment on percutaneous absorption of radioactive 17beta-estradiol was performed. RESULTS AND DISCUSSION: The simulation results agree with the experimental data. CONCLUSION: The use and power of the presented approach in studying the process of transepidermal drug delivery were demonstrated.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.835
Threshold uncertainty score0.868

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.177
GPT teacher head0.495
Teacher spread0.318 · 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