The Proposed PASI-HD Provides More Precise Assessment of Plaque Psoriasis Severity in Anatomical Regions with a Low Area Score
Bibliographic record
Abstract
The Psoriasis Area and Severity Index (PASI) is the most widely used clinical measure in clinical trials to assess disease severity of plaque psoriasis. However, the PASI is not a precise measure of severity with less precision when the regional area of involvement is < 10% of the BSA of a specific anatomical region. Degradation of precision results from the area score defaulting to '1' when the area of involvement within an anatomical region falls between 0% and 10% of the BSA for a given anatomical region. We describe a modification to the PASI, termed PASI-high discrimination (PASI-HD), for determination of more accurate psoriasis severity in body regions where < 10% of the body surface area is affected. The methodology for assessing disease severity in these conditions is described.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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".