Clarifying the Barriers to Optimal Healthcare for Persons with Inflammatory Arthritis
Bibliographic record
Abstract
Our research group investigated reasons for provision of suboptimal healthcare for persons with rheumatoid arthritis (RA) within the McGill University health network. In light of the recent article by Graydon and Thompson1, and the accompanying editorial by Harrington2, we report some of our preliminary findings. Recent work by Feldman, et al 3 suggested low rates of rheumatology referral for persons with suspected RA in Quebec, so we began with a series of focus group discussions to investigate reasons for this phenomenon. We conducted separate focus groups for major stakeholders (patients, family physicians, rheumatologists, allied healthcare providers, and administrative healthcare decision-makers). We had 3 focus groups for family physicians, with a total of 13 participants (9 men, 4 women). Across the stakeholder groups, commonly emerging themes included the value of communication (between physicians and patients, and between healthcare providers), education (of patients, healthcare providers, and the general community), and adequate … Address reprint requests to Dr. S. Bernatsky, Division of Clinical Epidemiology, Research Institute of the McGill University Health Centre, 687 Pine, Avenue West, V-Building, Montreal, Quebec H3A 1A1, Canada. E-mail: sasha.bernatsky{at}mail.mcgill.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 | 0.010 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.002 | 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".