Bibliographic record
Abstract
Time passes swiftly and is irrecoverable. In Love in the Time of Cholera , Gabriel García Márquez uses cholera as an analogy for the physical and emotional burdens caused by longing and lovesickness. Just as Florentino Ariza suffers physical and emotional pains from his longing for Fermina Daza, as one might suffer from a disease like cholera, in this issue, Katz and Ye tell a story of longing for equal access to rheumatology services.1 In this story, female individuals suffer the wait, and as time passes for people with rheumatic diseases, the disease will progress, and their prognoses worsen.2 The importance of understanding sex and gender differences in health and healthcare is established, as is the commitment to ensuring that research is conducted inclusively and equitably by funders in Canada and worldwide. Accordingly, the number of articles documenting the existence or absence of inequities between people according to their sex and gender should be increasing. In this issue of The Journal of Rheumatology , Katz and Ye share important results from Alberta, Canada, about the inequalities between biological sexes in access to rheumatology services.1 Concerningly, they found that female individuals and younger people experienced increased wait times for their first appointment with a rheumatologist during the coronavirus disease 2019 (COVID-19) pandemic.1 Timely access to care is critical to achieving optimal outcomes for people with arthritis and other rheumatic diseases, and ensuring equitable access to services is essential to meet the accessibility criterion of the Canada Health Act.3 The study by Katz and Ye1 adds to a body of literature, with mixed conclusions on the differences in wait times for a first rheumatologist visit and in treatment for … Address correspondence to M. Harrison, Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver Campus, 4625-2405 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada. Email: mark.harrison{at}ubc.ca.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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".