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Record W2114412364 · doi:10.1503/cmaj.060361

A bibliometric analysis by geographic area of published research in several biomedical fields, 1995-2003

2006· article· en· W2114412364 on OpenAlexvenueaboutno aff
Matthew E. Falagas, Argyris Michalopoulos, Ioannis A. Bliziotis, Elpidoforos S. Soteriades

Bibliographic record

VenueCanadian Medical Association Journal · 2006
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsnot available
Fundersnot available
KeywordsGross domestic productBibliometricsEpidemiologyImpact factorMEDLINEProductivityPopulationPublic healthMedicineLibrary scienceDemographyEnvironmental healthPolitical scienceEconomic growthComputer sciencePathologySociologyEconomicsLaw

Abstract

fetched live from OpenAlex

We summarized the findings of several studies of ours to compare the quantity and quality of published research from around the world for the years 1995 to 2003. We evaluated the number of articles published and their mean journal impact factor. We also studied the research productivity of various areas adjusted for gross domestic product (GDP) and population. We found that Western Europe leads the world in published research on infectious diseases-microbiology (82,342 articles [38.8%]) and in cardiopulmonary medicine (67,783 articles [39.5%]), whereas the United States ranks first in the fields of preventive medicine, public health and epidemiology both in quantity (23,918 articles [49.1%]) and quality of published papers. However, after adjustments for GDP, Canada ranked first, with the United States and Oceania following closely behind. All of the developing regions had only small research contributions in all of the biomedical fields examined.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.995
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0970.178
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.171
GPT teacher head0.468
Teacher spread0.298 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainEvaluation
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

Citations69
Published2006
Admission routes2
Has abstractyes

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