Open access publishing in health and social care simulation research – Advances in Simulation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although simulators have been used in healthcare education for hundreds of years, it is really only in the last thirty years that research with and about simulation has grown, and this growth has been exponential. The research has been diverse with respect to intent, simulation modality and context. It has been descriptive, experimental, evaluative, explanatory and exploratory, meaning the methodologies and methods have drawn from quantitative, qualitative and mixed methods research approaches. Researchers and their audiences are also diverse and include simulation practitioners, health and social care professionals and educators, psychologists, sociologists, biomedical scientists, engineers, information technologists, economists, programme evaluators, policy makers and others. Within this context Advances in Simulation takes its place as an open access scholarly publication at BioMed Central. Advances in Simulation will provide a forum for all to share scholarly research, ideas, policies and practices that advance the uses and theories of simulation in the health and social care community. Our journal fulfils an aspiration of the Executive of the Society in Europe for Simulation Applied to Medicine (SESAM), under the leadership of immediate Past President, Dr Ralf Krage and current President, Prof Antoine Tesniere. As Editor in Chief, I am granted editorial independence and together with the Senior Editors, Dr Peter Dieckmann (Denmark), Prof Tanja Manser (Germany) and Prof Ryan Brydges (Canada), we are charged with the responsibility of shaping the forum offered by Advances in Simulation. Our Editorial Board [1] comprises individuals representing the breadth of simulation research, development, policy and practice experience described above. We have a multi-layered
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.
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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.019 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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 it