Medical Student Research Journals: The International Journal of Medical Students (IJMS) Legacy
Bibliographic record
Abstract
The International Journal of Medical Students (IJMS) has emerged over the past decade as a critical platform for showcasing medical student innovation and experiences. Though the work of trainees has historically been undervalued and over scrutinized, the IJMS is committed to highlighting the immense capacity for novel and robust research in this cohort. Thus, supporting an upcoming generation of leaders in medicine and academia to gain confidence in their work and contribute positively to the scientific community. In this issue of the IJMS, we are proud to present 16 articles from the Americas, Europe, Asia, and Africa. Original research articles cover a breadth of topics, including medical training, impacts of the COVID-19 pandemic on teaching and communication, pediatric respiratory illness, gender equity in medicine, understudied illnesses, and cardiovascular disease. The IJMS is proud to feature first-hand experiences of medical trainees in each issue. Accordingly, in the present issue perspectives of six medical students are outlined following unique and career-altering experiences. From working in palliative care to international outreach program, local vaccination initiatives, and the creation of a student-oriented research and innovation council in India. The IJMs extends our gratitude to our contributors, team, and readers for another remarkable issue.
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 | 0.161 | 0.155 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.036 | 0.008 |
| Research integrity | 0.000 | 0.011 |
| Insufficient payload (model declined to judge) | 0.032 | 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; 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".