Advancing Research Through Early-Career Scientists’ Publications and Training the Next Generation of Medical Editors: The First 10-Years of the International Journal of Medical Students
Bibliographic record
Abstract
The International Journal of Medical Students (IJMS) has reached a new milestone. This historic issue will mark the final publication for the IJMS in the first 10-years of uninterrupted publications.The IJMS started following a discussion in 2009 at an international medical student congress where a conversation pertaining to student research was held. The discussion centered around the need for medical students to be acknowledged for their research, which in turn would lead to an improved research impact for the next generation in the medical-scientific community. By 2013 the ideas from the discussion at the congress had reached fruition and the IJMS published its first issue.
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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 | 0.071 | 0.125 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.042 | 0.023 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.011 | 0.019 |
| Insufficient payload (model declined to judge) | 0.025 | 0.010 |
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".