Bibliometric Assessment of the Global Scientific Production of Nitazoxanide
Bibliographic record
Abstract
INTRODUCTION: Nitazoxanide is a member of a new class of drug, thiazolides, and it was discovered in 1984 with antimicrobial activity effect against anaerobic bacteria, Hepatitis virus, protozoa, and helminths. METHODS: A bibliometric study on four databases (1984-2016) - Medline, Scopus, LILACS, and SciELO - characterizing the global scientific production of nitazoxanide. We determined the quantity, quality (number of citations), and types of studies developed by each country, characterizing them by years, international cooperation, development, place of publication, authors (with its H-index), and groups with higher impact. RESULTS: There were 512 articles in Medline - the higher scientific production is from the USA (19.71%), Switzerland (7.51%), and Mexico (7.27%). There were 1,440 articles in Scopus - from the USA (8.98%), Mexico (2.13%), and India (1.65%). There were 405 articles in LILACS - from Mexico (4.69%), the USA (4.2%), and Peru (2.47%). There were 47 articles in SciELO - from Brazil (34.04%), Venezuela (21.28%), and Colombia (14.89%). The H-index of nitazoxanide is 75 - the USA (26), Egypt (12), and Canada (10) were the countries contributing more with that. CONCLUSIONS: Nitazoxanide research has been highly important. Nevertheless, it is relatively limited when compared with other drugs. Its research has been led by the USA, as revealed in this bibliometric assessment. Although some developing countries, where it is used especially for protozoa and helminths, probably have its influence, and this explains the fact that Mexico and India, among others, are the top countries in the scientific production of this anti-infective agent. This bibliometric study evidenced a relatively low number of publications, however, it has been increased in recent years.
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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 | 0.011 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.159 | 0.189 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".