Bibliographic record
Abstract
We are thrilled to announce the launch of the Salamat Academic & Research Journal (SARJ), an open-access publication of Jami University dedicated to advancing medical and health sciences. SARJ, licensed by Afghanistan's Ministry of Higher Education in 2024, provides a prestigious, accessible forum for the publication of high-quality, peer-reviewed research. This journal is the latest initiative in Afghanistan's storied commitment to medical education, which began with the establishment of the Faculty of Medicine in Kabul in 1932 [1]. SARJ extends this legacy, offering Afghan and global researchers a platform for innovation in medical sciences. The establishment of SARJ also builds on the foundation of scholarly communication in Afghanistan. The Afghan Medical Journal (AMJ), initiated in 1956 by Kabul University, pioneered medical publication in Afghanistan, creating one of the nation’s first platforms for sharing scientific findings [2]. AMJ, originally published from 1956 to 1963, laid the foundation for scholarly medical publishing in Afghanistan and has recently been revitalized to continue its mission. The newly relaunched AMJ is now an official national and international open-access peer-reviewed journal. Initiatives like SARJ proudly follow in AMJ's footsteps, contributing to a robust and accessible platform for advancing medical research and public health in Afghanistan [3]. SARJ honors this tradition by fostering an inclusive academic community that makes quality medical research available to all, from students and researchers to healthcare practitioners.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.018 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.048 | 0.029 |
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".