Pathway to Dry Skin Prevention and Treatment
Bibliographic record
Abstract
BACKGROUND: This article presents an evidence-supported clinical pathway for dry skin prevention and treatment. OBJECTIVE: The development of the pathway involved the following: a literature review was conducted and demonstrated that literature on dry skin is scarce. To compensate for the gap in the available literature, a modified Delphi method was used to collect information on prevention and treatment practice through a panel, which included 10 selected dermatologists who currently provide medical care for dermatology patients in Ontario. An advisor experienced in this therapeutic area guided the process, including a central meeting. Panel members completed a questionnaire regarding their individual practice in caring for these patients and responded to questions on assessment of dry skin etiology, frequency of skin care visits for consultation and follow-up, assessment, and referral to other specialties. The panel members reviewed a summary of all responses and reached a consensus. The result was presented as a clinical pathway. CONCLUSION: The panel concluded that our current awareness of dry skin and therefore prevention and effective treatment is limited; that identifying dry skin and its clinical issues requires tools such as clinical pathways, which may improve patient outcomes; and that additional research on dry skin etiology, prevention, and treatment is necessary.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".