Pediatric rheumatology education: the virtual frontier a review
Bibliographic record
Abstract
BACKGROUND: Many children with rheumatic and musculoskeletal diseases are unrecognized. Identifying these children requires health care provider awareness, knowledge, and skills to recognize disease features and how (and when) to refer to specialist care. The aim of this paper is to highlight the need for better access to health care, review the essential role that education and virtual care play to address unmet need in low resource areas and especially to expand workforce capacity. Using collaborative partnerships, virtual platforms, and innovative assessment methods, musculoskeletal care and education can be delivered to reach a greater audience than ever before. Increased awareness through multiple initiatives and readily available resources are imperative to improve global rheumatology care. CONCLUSION: The needs of children with rheumatic diseases and musculoskeletal conditions are vastly underserved around the world resulting in preventable morbidity and mortality. Expanded implementation of virtual education and e-health care platforms provides an opportunity to increase access to care for children globally.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.012 |
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; both teacher heads agree on what is shown here.
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".