Dr. Mease et al reply
Bibliographic record
Abstract
To the Editor: We thank Dr. Maguire et al1 for their interest in and appreciation of our study from the Corrona Psoriatic Arthritis/Spondyloarthritis Registry comparing patient characteristics and disease burden between men and women with axial spondyloarthritis (axSpA).2 Dr. Maguire and colleagues raised a number of interesting questions around the causal relationship between the higher prevalence of depression and decreased work productivity we observed in women in our study. While we were unable to directly address these questions in the Registry, we agree and appreciate that these are important research priorities for future investigations. As we noted in our study, limited information exists on the overall disease burden of axSpA in women in the US, as women are generally underrepresented in clinical studies. Further, much of our … Address correspondence to Dr. P.J. Mease, Seattle Rheumatology Associates, 601 Broadway, Suite 600, Seattle, WA 98122, USA. Email: pmease{at}philipmease.com.
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 | 0.003 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.032 | 0.033 |
| Insufficient payload (model declined to judge) | 0.009 | 0.009 |
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".