Bibliographic record
Abstract
Acne, one of the most common skin diseases, affects approximately 85% of the adolescent population, and occurs most prominently at skin sites with a high density of sebaceous glands such as the face, back, and chest. Although often considered a disease of teenagers, acne is occurring at an increasingly early age. Rosacea is a chronic facial inflammatory dermatosis characterized by flushing (or transient facial erythema), persistent central facial erythema, inflammatory papules/pustules, and telangiectasia. Both acne and rosacea have a multifactorial pathology that is incompletely understood. Increased sebum production, keratinocyte hyper-proliferation, inflammation, and altered bacterial colonization with Propionibacterium acnes are considered to be the underlying disease mechanisms in acne, while the multifactorial pathology of rosacea is thought to involve both vasoactive and neurocutaneous mechanisms. Several advances have taken place in the past decade in the research field of acne and rosacea, encompassing pathogenesis and epidemiology, as well as the development of new therapeutic interventions. In this article, we provide an overview of current perspectives on the pathogenesis and treatment of acne and rosacea, including a summary of findings from recent landmark pathophysiology studies considered to have important implications for future clinical practice. The advancement of our knowledge of the different pathways and regulatory mechanisms underlying acne and rosacea is thought to lead to further advances in the therapeutic pipeline for both conditions, ultimately providing a greater array of treatments to address gaps in current management practices.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".