The Brigham Scalp Nail Inverse Palmoplantar Psoriasis Composite Index (B-SNIPI): A Novel Index to Measure All Non-plaque Psoriasis Subsets
Bibliographic record
Abstract
Psoriasis is a chronic inflammatory disease that encompasses a large spectrum of clinically distinct subtypes. Although chronic plaque psoriasis is reported as the most common form of psoriatic skin disease, there is growing evidence that other variants including scalp, nail, inverse, and palmoplantar psoriasis are prevalent, undertreated, and associated with significant impairment in quality of life. Currently, the Psoriasis Area and Severity Index (PASI) is the standard to assess psoriasis severity as well as response to treatment; however, the PASI has several limitations. In response to this need and as a complementary objective measure to the PASI, we created the Brigham Scalp Nail Inverse Palmoplantar Psoriasis Composite Index (B-SNIPI), based on patient-surveyed, patient-reported outcomes equally weighted with physician assessment of disease activity. Herein we summarize the B-SNIPI as presented at the 2013 Annual Meeting of the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA).
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".