Bibliographic record
Abstract
On June 1, 2006, the trade associations representing the personal care industry of the European Union, the U.S., Japan and South Africa agreed on an International Sunscreen Protection Method. What will this mean? Sunscreens are regulated throughout the world either as cosmetics, over‐the‐counter (OTC) drugs which do not require a governmental pre‐approval or OTC drugs that require a pre‐approval before they are placed on the market. Regardless of how they are regulated, all of these product regulations are very similar concerning sunscreens! Each country has a pre‐approved list of permitted UV filters, an accepted method of running efficacy by SPF determination, and regulated labels. Some countries have approved methods for UVA claims and water‐resistance testing. The latest changes are in Australia, where some sunscreens will be regulated as cosmetics based on SPF and claims, and Canada, where some sunscreens will be regulated as Natural Health Products depending on their actives! And now here comes a new variable, the harmonized SPF method. What confusion! This paper will cover the different SPF test methods (Harmonized, Australia, and US‐FDA) along with the formulations of reference standards, currently approved UVA methods, water‐resistant testing, some labeling requirements and finally a brief review of cGMPs and other requirements for the U.S. It will have an update of the recent changes in regulations and cover the approved UV filters permitted in the U.S., EU, Japan, Canada and Australia as well as their maximum use level and correct ingredient designation. There is also a master cross reference list by INCI designation.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.032 | 0.018 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".