Development and Evaluation of a Rosacea Screening Instrument (Rosascreen)
Bibliographic record
Abstract
BACKGROUND: There are no current instruments to facilitate population screening for rosacea. OBJECTIVE: To develop and evaluate a screening instrument for rosacea applicable for population surveys. METHODS: A rosacea-specific screening instrument (Rosascreen), consisting of a subject-completed questionnaire and screening algorithm, was developed based on current diagnostic criteria for rosacea. Three iterations were pilot tested and refined for clarity and sensitivity in adult outpatients with and without rosacea. RESULTS: Three subject groups were consecutively evaluated with iterations of the questionnaire at each centre (overall N = 121). The final version had a sensitivity of 93% to 100% for key diagnostic criteria, and use of the algorithm had a sensitivity of 100% for detection of rosacea and specificity of 63% to 71%. Most subjects found the questionnaire easy to understand and complete. CONCLUSION: Rosascreen, a subject-completed questionnaire and diagnostic algorithm, is a highly sensitive screening instrument that may facilitate estimation of rosacea prevalence in general populations.
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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 | 0.024 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".