A survey of clinicians regarding preferred severity assessment tools for hidradenitis suppurativa
Bibliographic record
Abstract
Hidradenitis suppurativa (HS) is a chronic, relapsing-remitting skin disease characterized by inflammatory nodules, abscesses, and tunnels involving intertriginous sites. 1 HS outcome measures have traditionally relied on lesion counts, the accuracy of which has recently been questioned.2 In 2016, Ingram et al. reviewed 12 randomized-controlled trials in HS and reported that 90% of the 30 outcome measure instruments used lacked validity data.3 Since then, additional validation has been completed and new outcome tools have been proposed.In consequence of doubts raised regarding lesion counts, tools relying on body surface area (BSA) and signs of inflammation have recently been proposed, including the Severity and Area Score for Hidradenitis (SASH) 4 , and Hidradenitis Suppurativa Area and Severity Index
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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 | 0.006 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".