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Record W3080828263 · doi:10.1097/der.0000000000000666

Nickel: Intrinsic Skin Sensitization Potency and Relation to Prevalence of Contact Allergy

2020· article· en· W3080828263 on OpenAlexvenueno aff
David A. Basketter

Bibliographic record

VenueDermatitis · 2020
Typearticle
Languageen
FieldMedicine
TopicContact Dermatitis and Allergies
Canadian institutionsnot available
Fundersnot available
KeywordsPotencySensitizationSkin sensitizationMedicineNickel allergyContact allergyAllergyAllergenAllergic contact dermatitisIn vivoImmunologyContact dermatitisToxicologyPharmacologyIn vitroBiotechnologyBiologyBiochemistry

Abstract

fetched live from OpenAlex

Nickel remains the most commonly identified contact allergen. However, it has proven difficult to demonstrate significant skin-sensitizing activity for nickel in toxicology tests, which typically have indicated a weak skin sensitization potential. Information indicates that in vivo assays are not predictive of dermal sensitization hazard or potency for nickel due to a human-specific mechanistic route for nickel sensitization that animals lack. A similar rationale will apply to in vitro alternatives-although these currently have limited ability to determine intrinsic potency. Generally, in silico methods are not designed for metal allergens and cannot contribute to the analysis. For ethical reasons, human experimental work has been limited, with a single study suggesting moderate potency. Accordingly, it seems reasonable to conclude that the high frequency of contact allergy to nickel in humans is a function of both its intermediate potency coupled with a high level of dermal exposure, particularly to damaged/inflamed skin.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.011
GPT teacher head0.229
Teacher spread0.218 · 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 designObservational
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

Citations19
Published2020
Admission routes1
Has abstractyes

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