Spectral Homeostasis – The Fundamental Requirement for an Ideal Sunscreen
Bibliographic record
Abstract
Sunscreen application to UV-exposed skin is promoted to prevent skin cancer and sun damage, within a comprehensive photoprotection strategy that also includes sun avoidance and wearing UV protective clothing. The benefits of sunscreen are verified in preventing sunburn but appear to be largely presumptive in skin cancer prevention. Contemporary science establishes UVA as a primary driver of melanoma and photoaging. Consequentially, the traditional UVB-skewed protection of sunscreens provides an intellectual and logical explanation for rising skin cancer rates and, in particular, their failure to protect against melanoma. Better protection could be achieved with more balanced UVB/UVA sunscreens, toward spectral homeostasis protection. Greater balanced protection has another advantage of attenuating fewer UVB rays, which aid synthesis of vitamin D and nitric oxide. Percutaneous absorption of Soluble Organic UV Filters leads to systemic exposure, which becomes the relevant safety consideration. It is minimized by selecting Insoluble UV Filters with low absorption potential from a molecular weight above 500 Da. The filters must also be very hydrophilic, very lipophilic, or consist of particles. The risk-benefit ratio is a medical imperative, more so for cosmetics or sunscreens, since in principle there should be no risk from their use. The production of ideal sunscreens that mimic the effective, balanced UVB/UVA attenuation of textiles and shade is now possible, while maintaining an acceptable therapeutic margin of safety in humans and a favorable ecologic profile. Sunscreens with a favorable risk-benefit ratio and good esthetic properties or other consumer-friendly attributes will improve compliance and may achieve substantial clinical benefits.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".