International gastroenterology research: subject areas, impact, and funding
Bibliographic record
Abstract
AIMS: To examine the volume and potential impact of gastroenterology research outputs from 1985 to 1998 from 14 developed countries; the overlap with research in cancer, infectious diseases, and genetics; and the funding sources for this research. To determine if countries' research outputs correlated with their burden of corresponding diseases and inputs to their research. METHODS: Selective retrieval of papers from the Science Citation Index and manual look up of a sample to determine funding sources. Classification of journals by four categories of research level (clinical/basic) and potential impact (low/high). RESULTS: Gastroenterology represents about 8% of world biomedical research but over 11% in Italy, Japan, and Spain. Its potential impact is highest (but declining) for the USA. It has increased noticeably in most European countries, particularly in Finland. Gastroenterology research has become more clinical in Japan, Spain, Australia, and the Netherlands but more basic in Canada, Germany, Finland, Israel, and South Africa. Funding comes primarily from national governments, followed by national private non-profit sources and industry but little industrial funding occurs in some countries. There is a strong and positive correlation between reported deaths from gastrointestinal neoplasms and countries' outputs of research in gastrointestinal oncology. CONCLUSIONS: Bibliometric analysis can reveal differences between countries in their research in a subject when a common methodology is applied to an international database. Variations in research methods in different countries can plausibly explain some of the variation in the potential impact of the work.
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 | 0.013 | 0.078 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.078 | 0.189 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".