Bibliographic record
Abstract
BACKGROUND: Alopecia areata is a nonscarring hair loss characterized by well-circumscribed patchy areas, most often on the scalp. The inflammatory cytokine tumor necrosis factor alpha (TNF-alpha), has been connected with the development of alopecia areata in vivo; thus, the TNF-alpha inhibitors have been cited as possible treatments for this autoimmune condition. OBJECTIVE: We report a case of alopecia areata that developed in a 52-year-old woman who was recently started on adalimumab for treatment of her psoriatic arthritis. RESULTS: We discuss the previously published cases in the literature linking alopecia areata to TNF-alpha inhibitor administration. Our case is the first report of a new-onset alopecia areata following adalimumab. CONCLUSIONS: Even though TNF-alpha is implicated in causing alopecia areata, TNF-alpha inhibitors have paradoxically been associated with new cases of alopecia areata. It is possible that TNF-alpha may not be involved in the pathogenesis of alopecia areata, as in vitro studies have suggested.
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 | 0.001 |
| 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".