Worldwide research productivity in the field of psychiatry
Bibliographic record
Abstract
BACKGROUND: The field of psychiatry has seen significant progress in recent years due to worldwide contributions. National productivity, however, in the field of psychiatry is still unclear. In our study, we investigated contributions of individual nations to the field of psychiatry. METHODS: The Web of Science was used to perform a search from 2011 to 2015 on the subject category "psychiatry". The total number of articles, citations and the per capita numbers were obtained to analyze the contributions of different countries. RESULTS: In psychiatry journals from 2011 to 2015, 84,760 articles were published worldwide. The most productive world areas were North America, East Asia, Europe and Oceania. The percentage of articles published in high-income countries was 87.77%, middle-income countries published 12.07%, and lower-income published 0.16%. Most articles were published by the United States (32.68%); the United Kingdom was next (8.59%), which was followed by Germany (6.77%), Australia (5.87%), and Canada (4.9%). The country with the highest number of citations (243,394) was the United States. A positive correlation was found between the population/GDP and the number of publications (P < 0.01). Australia ranked the highest when normalized to population size, and the Netherlands and Norway were next. The Netherlands ranked highest, followed by Israel and Australia when adjusted for GDP. CONCLUSIONS: The authorship of most of the psychiatry articles was from high-income countries and few papers came from low-income countries. The most productive country was the United States. However, when normalized to population size and GDP, some European and Oceania countries were most productive.
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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 | 0.023 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.027 | 0.035 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 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".