Bibliometric profile of the global scientific research on autism spectrum disorders
Bibliographic record
Abstract
BACKGROUND: Autism spectrum disorders (ASD) are a group conditions classified as neuro-developmental disorders. Research activity on ASD is important for all countries since such disorders have both social and health consequences. The objective of this study was to analyze research output on ASD during the period 2005-2014. METHODS: All articles relevant to ASD plus all articles published in autism journals were retrieved using Scopus database. VOSviewer software was used to create density and network visualization maps. Bibliometric indicators were investigated by analyzing annual research output, languages, countries, institutions, journals, title terms, highly cited articles, and co-authorship relations. RESULTS: A progressive annual growth of ASD research was observed from 2005 to 2014. During this period, a total of 18,490 articles were retrieved. The majority of these articles was published in Journal of Autism and Developmental Disorders with 48,416 citations and an average citation of 23.59 citations per article. The countries that published the largest number of articles were the United States (US) (n = 8594; 46.48 %), United Kingdom (n = 2430; 13.14 %) and Canada (n = 1077; 5.8 %). International collaborations produced 30.18 % of the articles published by top 10 productive countries. King's College London (UK) ranked first in number of publications and total citations. The top 10 list of productive institutions was dominated by US academic and research institutions. More than half of the highly cited articles were in the field of molecular genetics. Articles with more than 50 citations were published mainly by authors from USA, UK and Canada. CONCLUSIONS: There is a worldwide growth of publications on ASD led by countries in Northern America and Europe. Retrieved articles were published in a wide range of journals. Molecular genetics of ASD is the primary hot topic on ASD. For some leading countries, intra country collaboration is dominant.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.008 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.143 | 0.194 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".