Bibliographic record
Abstract
Hydroquinone has been successfully used to treat hyperpigmentation disorders for many years. Recently, new formulations containing hydroquinone have become available, including Lustra and Lustra-AF (Medicis). These products also contain glycolic acid 2%, an active antioxidant system (ascorbyl palmitate and tocopherol acetate), and moisturizers. Lustra-AF also contains a broad-spectrum sunscreen. Alustra contains a stabilized, high-concentration of retinol. The above formulations inhibit melanogenesis, stimulate epidermal desquamation, inhibit free radical-mediated photodamage and restore the antioxidant reservoir. The addition of retinoids may facilitate epidermal penetration of hydroquinone and prevent its oxidation. Comparative studies have shown that these agents can be effective in reducing blotchiness, mottled hyperpigmentation, post-inflammatory hyperpigmentation, and surface roughness. In addition, these formulations have been generally well tolerated with patients rarely reporting mild-to-moderate adverse events such as dryness, redness, or peeling of the skin.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.029 | 0.007 |
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".