Contribution Of Hacettepe University Faculty Of Medicine To The World'S Biomedical Literature (1988-1997)
Bibliographic record
Abstract
The contribution of Turkish researchers to sciences is increasing. Turkish scientists publishedmore than 6.000 articles in 1999 in scientific journals indexed by the Institute for Scientific Information’s Science Citation Index, which puts Turkey to the 25th place in the world rankings interms of total contribution to science. The number of biomedical publications authored by Turkishscientists is increasing faster than that of engineering and other non-medical sciences, whichmight be one of the main causes of the steep rise in Turkey’s rankings that we have been witnessing in recent years. More specifically, researchers affiliated with Hacettepe Universityproduce almost a quarter of all the biomedical publications of Turkey that appear in international biomedical literature. In this paper, we report the findings of the bibliometric characteristics (authors and affiliations, medical journals and their impact factors, among others) of a total of 1.434 articlespublished between 1988 and 1997 by scientists affiliated with Hacettepe University Faculty ofMedicine and indexed in MEDLINE, a well-known biomedical bibliographic database.
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 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 | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.037 | 0.050 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".