A Bibliometric Analysis of Scorpionism Epidemiology in Tropical Health
Bibliographic record
Abstract
Scorpionism has driven studies around the world on data relating to epidemiological and clinical aspects in humans. From this perspective, a bibliometric review was carried out to analyze the historical and evolutionary construction of the epidemiology of scorpionism to identify the main authors, journals, countries and years of emphasis, as well as the most cited studies and most frequent terms, through quantitative and qualitative data extracted from the manuscripts. The review also investigated studies that explored the association of the topic with environmental, climatic and anthropogenic factors. The analysis was based on publications indexed in the Scopus database, covering the period from 1952 to 2022. The result of the global analysis, based on 145 articles, demonstrates a growing evolution of the topic. Brazil (17.93%) and Iran (17.24%) emerged as the most productive countries in terms of research production. However, the US, Mexico, Algeria and Canada (11.11%) have the most substantial collaborative efforts. The magazine “Toxicon” stands out as the predominant source of scientific dissemination (25%). Only eight authors have unique authorship and the author Semlali Ilham emerged as the most prominent. Universities were the affiliations with the highest productivity. The results of the metadata extraction analysis, based on a sample of 14 documents, revealed consistent and sustained epidemiological data since 1982. Of these, only one study (7.1%) from French Guiana used environmental variables to elucidate data on the occurrence of scorpion stings. The genera Tityus, Centruroides and Androctonus emerged as the most representative among the works compiled and evaluated.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.289 | 0.417 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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; both teacher heads agree on what is shown here.
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".