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Record W2119762760 · doi:10.1136/gut.49.2.295

International gastroenterology research: subject areas, impact, and funding

2001· article· en· W2119762760 on OpenAlexaboutno aff
Grant Lewison, Jonathan Grant, Plm Jansen

Bibliographic record

VenueGut · 2001
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsnot available
FundersEuropean CommissionCilagWellcome TrustWorld Health Organization
KeywordsMedicineCitationClinical researchSubject (documents)Political scienceInternal medicineLibrary science

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.265
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.353
GPT teacher head0.532
Teacher spread0.179 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations56
Published2001
Admission routes1
Has abstractyes

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