Improving addiction patients’ quality of life through exercise
Bibliographic record
Abstract
I conjunction with publication records, more and more weight is put on citations in determining research productivity by individuals, universities and even nations. This topic is widely discussed and debated within psychiatry but without much empirical evidence to draw on. We felt it was important to examine this issue by analyzing publication output and citations in a range of psychiatry journals. We investigated research productivity and citation practices at both country and university level. We found large differences between and within countries in terms of their research productivity in psychiatry. In addition, the ranking of countries and institutions differed widely by whether productivity was assessed by total research records published, overall citations these received, or citations per paper. We found that most publications came from the USA, with Germany being second and UK third in productivity. USA articles received most citations and the highest citation rate with an average 11.5 citations per article. The UK received the second highest absolute number of citations, but came fourth by citation rate (9.7 citations/article), following the Netherlands (11.4 citations/article) and Canada (9.8 citations/article). Within the USA, Harvard University published most articles and these articles were the most cited, on average 20.0 citations per paper. In Europe, UK institutions published and were cited most often. The Institute of Psychiatry/Kings College London was the leading institution in terms of number of published records and overall citations, while Oxford University had the highest citation rate (18.5 citations/record). The choice of measures of scientific output could be important in determining how research output translates into decisions about resource allocation.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".