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Record W4242003663 · doi:10.1201/9781003075424-4

Dermal Penetration

2020· book-chapter· en· W4242003663 on OpenAlexaff
Richard P. Moody

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsHealth Canada
Fundersnot available
KeywordsPenetration (warfare)EngineeringOperations research

Abstract

fetched live from OpenAlex

This chapter examines the advantages and disadvantages of the methods employed, with particular emphasis on data originating from the author's laboratory and includes mention of the new Automated In Vitro Dermal Absorption method that employs small autosampler vial inserts to hold skin tissue samples for dermal testing. It reviews standard in vivo and in vitro test methods used in the laboratory and attempts to demonstrate where these methods may fail to provide accurate data. The efficacy of dermal absorption of a pesticide can be expressed quantitatively as the percentage of the total topically applied dose of the pesticide that becomes bioavailable via the dermal absorption route, including intercellular, intracellular, and transappendageal components. Dermal absorption studies undergo critical evaluation by both government and industry to ensure that the data acquired from these studies are applicable for predicting human occupational and bystander systemic exposure to pesticides.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.099
Threshold uncertainty score0.331

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0990.059

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 head0.024
GPT teacher head0.255
Teacher spread0.231 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2020
Admission routes1
Has abstractyes

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