Top ten research priorities in global burns care: findings from the James Lind Alliance Global Burns Research Priority Setting Partnership
Bibliographic record
Abstract
Burns are a global issue that can result in lifelong multimorbidities and disproportionately affect people in low-resource settings. Prioritising research of importance to patients and health-care professionals improves evidence-based care. This prioritisation setting partnership was undertaken in global burn care (focusing on thermal non-electrical burns) by establishing a James Lind Alliance research priority setting partnership. Over 2 years, two online multilingual surveys with patients, carers, and clinicians, 16 interviews, and a virtual priority setting workshop were conducted to identify and prioritise questions for research. Survey responses were received from participants in 88 countries (1617 survey one respondents; 630 survey two respondents). A short-list of 19 research priorities were ranked at an online workshop attended by 28 participants (14 health-care professionals, ten burn survivors, and four carers or advocates) from 15 countries to produce the final top ten research priorities. These priorities provide opportunities for researchers, funders, and clinicians to shape the future of burns research and improve burns care 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 | 0.013 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| 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".