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Record W2995974657 · doi:10.1097/der.0000000000000429

Parabens

2019· review· de· W2995974657 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueDermatitis · 2019
Typereview
Languagede
FieldMedicine
TopicContact Dermatitis and Allergies
Canadian institutionsUniversity of OttawaHealth Sciences CentreSunnybrook Health Science CentreMcGill University Health Centre
Fundersnot available
KeywordsMedicineTraditional medicine

Abstract

fetched live from OpenAlex

Parabens have been widely used as preservatives in the cosmetics, food, and pharmaceutical industries for more than 70 years. Monitoring for paraben allergy closely followed with studies reporting paraben testing in standard screening fashion as early as 1940. The frequency of sensitivity to this widely used biocide has remained low and remarkably stable for many decades despite extensive use and progressive expansion of utilization worldwide. The authors select paraben mix as the (non)allergen of the year. Paraben reactions are quite uncommon and generally relevant. Parabens remain one of the least allergenic preservatives available. The unsubstantiated public perception of paraben safety has led to its replacement in many products with preservatives having far greater allergenic potential. This report reviews the well-established safety of parabens from an allergologic standpoint.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.609
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.098

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 head0.041
GPT teacher head0.305
Teacher spread0.264 · 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