Spanning three decades: global research wave and future prospects of broader autism phenotype—a visual researches by CiteSpace and VOS viewer
Bibliographic record
Abstract
Objectives: To conduct a comprehensive review of the literature pertaining to the broader autism phenotype, the paper endeavors to delineate the key research directions and topics, document the current research trends, and furnish insightful analyses and novel perspectives to foster future advancements in the field, with the aid of CiteSpace and VOS viewer. Methods: CiteSpace and VOS viewer are two kinds of software for visualizing citations that is intended to examine academic literature and identify possible sources of knowledge. The Web of Science Core Collection database was used to retrieve articles from 1994 to 2024 that discussed the autism phenotype in general. Following data collection, analyses were conducted using CiteSpace V.6.2.R4 (64-bit) on a number of topics, such as annual publication output, highly cited journals, affiliations with countries and institutions, eminent authors, cited references, and keywords. Knowledge maps, collaborative network analysis, cluster analysis, and strongest citation burst analysis were among the tools used to visualize the data. Results: A total of 1,075 articles about the broader autism phenotype were found. Roughly speaking, the annual number of publications is rising. With 546 articles on the subject, the United States is the nation with the greatest amount of authority and influence (centrality of 0.32), with England (218 articles) and Canada (115 articles) coming in second and third, respectively. The cited journals and institutions are mainly from the United States. The research consistently emphasizes the academic achievement and engagement of broader autism phenotype when analyzing the most cited references and authors. Conclusion: This study used CiteSpace to analyze the state of the larger autism phenotype field and then identified research frontiers and hotspots. As new findings are made, global trends in more thorough studies of the autism phenotype suggest that interest in these studies will only grow.
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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.029 | 0.039 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.004 |
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".