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Record W2951734567 · doi:10.1177/1203475419856611

Sunscreen Application, Safety, and Sun Protection: The Evidence

2019· review· en· W2951734567 on OpenAlexaffabout
Heidi Oi‐Yee Li, Sophia Colantonio, Andrea E. Dawson, Xing Lin, Jennifer Beecker

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2019
Typereview
Languageen
FieldMedicine
TopicSkin Protection and Aging
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsSun protectionMedicineSun protection factorSunscreening AgentsSun exposureSunburnEnvironmental healthSkin cancerDermatology

Abstract

fetched live from OpenAlex

Recently in Canada, there has been an effort to create consistent messaging about sun safety as there is a lack of up-to-date evidence-based guidelines regarding sun-protection measures. This review aimed to provide updated, evidence-based recommendations on sunscreen application, safety, and sun protection regarding the following topics for which there is clinical uncertainty: physical barriers, sunscreen properties, sunscreen application, and risk-benefit analysis.

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)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.002
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 head0.133
GPT teacher head0.360
Teacher spread0.227 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations115
Published2019
Admission routes2
Has abstractyes

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