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Record W1974201547 · doi:10.1016/j.yrtph.2014.05.013

Risk Assessment of residual monomer migrating from acrylic polymers and causing Allergic Contact Dermatitis during normal handling and use

2014· article· en· W1974201547 on OpenAlexaff
Mark Pemberton, Barbara S. Lohmann

Bibliographic record

VenueRegulatory Toxicology and Pharmacology · 2014
Typearticle
Languageen
FieldMedicine
TopicContact Dermatitis and Allergies
Canadian institutionsNexen (Canada)
FundersNational Institutes of HealthLG Chem
KeywordsLocal lymph node assayMethyl methacrylateSensitizationMonomerAllergic contact dermatitisToxicityPolymerChemistryPolymer chemistryAllergyOrganic chemistryMedicineImmunologySkin sensitization

Abstract

fetched live from OpenAlex

Acrylic, Poly Methyl Methacrylate (PMMA) based polymers are found in many industrial, professional and consumer products and are of low toxicity, but do contain very low levels of residual monomers and process chemicals that can leach out during handling and use. Methyl Methacrylate, the principle monomer is of low toxicity, but is a recognized weak skin sensitizer. The risk of induction of contact allergy in consumers was determined using a method based upon the Exposure-based Quantitative Risk Assessment approach developed for fragrance ingredients. The No Expected Sensitization Induction Level (NESIL) was based on the threshold to induction of sensitization (EC3) in the Local Lymph Node Assay (LLNA) since no Human Repeat Insult Patch Test (HRIPT) data were available. Categorical estimation of Consumer Exposure Level was substituted with a worst case assumption based upon the quantitative determination of MMA monomer migration into simulants. Application of default and Chemical-Specific Adjustment Factors results in a Risk Characterization Ratio (RCR) of 10,000 and a high Margin of Safety for induction of Allergic Contact Dermatitis (ACD) in consumers handling polymers under conservative exposure conditions. Although there are no data available to derive a RCR for elicitation of ACD it is likely to be lower than that for induction.

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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score0.840

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.013
GPT teacher head0.280
Teacher spread0.268 · 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 teacher head, 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

Citations30
Published2014
Admission routes1
Has abstractyes

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