Applying the phenotype approach for rosacea to practice and research
Bibliographic record
Abstract
BACKGROUND: Rosacea diagnosis and classification have evolved since the 2002 National Rosacea Society expert panel subtype approach. Several working groups are now aligned to a more patient-centric phenotype approach, based on an individual's presenting signs and symptoms. However, subtyping is still commonplace across the field and an integrated strategy is required to ensure widespread progression to the phenotype approach. OBJECTIVES: To provide practical recommendations that facilitate adoption of a phenotype approach across the rosacea field. METHODS: A review of the literature and consolidation of rosacea expert experience. RESULTS: We identify challenges to implementing a phenotype approach in rosacea and offer practical recommendations to overcome them across clinical practice, interventional research, epidemiological research and basic science. CONCLUSIONS: These practical recommendations are intended to indicate the next steps in the progression from subtyping to a phenotype approach in rosacea, with the goals of improving our understanding of the disease, facilitating treatment developments and ultimately improving care for patients with rosacea.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".