Bibliometric analysis of research relating to gonorrhea reported over the period 1980–2020
Bibliographic record
Abstract
Abstract Objective and Design: Gonorrhea is an important sexually transmitted disease that threatens public health in the 21st century. Aim of this study was to reveal the current status of literature data about gonorrhea. Methods: A scan of literature was performed on the Web of Science (WoS) database on 17 Aug 2021 to retrieve bibliometric data. The literature search was applied using the search term “gonorrhea” in article titles for the period January 1980–December 2020. Results: After applying all inclusion and exclusion criteria, 1068 articles remained for final evaluation. The number of articles published by year tended first to decrease and then to increase. According to the number of articles, the first three countries were the USA (n=660; 61.80%), England (n=107; 10.02%), and Canada (n=52; 4.87%). The journal with the highest number of articles were the Journal of Sexually Transmitted Diseases and Sexually Transmitted Infections. The Centers for Disease Control and Prevention organization in the United States produced the largest number of articles on gonorrhea during this specified time period. Conclusions: This holistic data evaluation of analysis of the findings, knowing the trend topics, understanding which topics are cited more, will be of benefit for authors conducting future research.
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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 | 0.010 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.181 | 0.218 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".