Scientific production of Leishmaniasis in PubMed: Impact of Iranian institutes
Bibliographic record
Abstract
A bibliometric study was carried out to analyze and visualize the scientific production of countries in the field of Leishmania during a period of 10 years. Only scientific profiles published in the journals which indexed in Medline through 2000-2009 were taken under consideration. All data was extracted from PubMed online. The study focused on the scientific production and productivity of Iranian institutes in the field of Leishmania. Analysis of data showed that English consisting 96.3% of total publications’ language is the dominate dominant language of publications. Brazilian authors with contributing 18.2% of total pubications in the field are the most prolific authors during the period of study, followed by authors from USA (16.1%), India (13%), UK (8.4%), Spain (5.6%), France (4.4%), Germany (3.9%), Canada (3.5%), and Iran (2.7%) respectiviely. The journal of “ Molecular and biochemical parasitology” is the most productive journal regarding to distributing the great number of publications in the field of Leishmani followed by “ Infection and immunity ” and “” Experimental parasitology ”. Among Iranian institutes “Pasteur Institute of Tehran” with contributing 30.1% of total publications from Iranian institute is the most productive institute in Iran followed by “ Tehran University of,Medical Sciences ” and “Shiraz University of Medical Sciences” contributing 20.3% and 18.7% of total publications from Iran respectively. Keywords : Leishmaniasis; Bibliometrics; Scientific production
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 | 0.007 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.090 | 0.133 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| 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".