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Record W2392690500

A bibliometric analysis of systematic review on tuberculosis at home and abroad

2013· article· en· W2392690500 on OpenAlexaboutno aff
Zhao Guo-bin

Bibliographic record

VenueXiandai yufang yixue · 2013
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsCitationTuberculosisChinaWeb of scienceCitation databaseBibliometricsSystematic reviewScience Citation IndexGrey literatureMedicineCitation analysisMEDLINELibrary scienceGeographyMeta-analysisPolitical scienceScopusPathology
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE To understand the progress in systematic review on tuberculosis at home and abroad over the last 10years through a bibliometric approach. METHODS Foreign literatures about systematic review on tuberculosis(2002-2011)were searched from the Web of science citation database, and the domestic literatures(2002-2011) were searched through the ISI Web of science citation database and several kinds of Chinese databases. The searching results were analyzed concerning the article numbers and the frequency of citation by publication year, institutions, authors, and periodical distribution.RESULTS Overall 269 foreign literatures and 109 Chinese literatures were found. The number of papers at home and abroad had increased significantly over the two or three years. Developed countries such as USA, Canada, England and Switzerland had played important roles in the systematic review on tuberculosis research in the world. The domestic literatures mainly concentrated in core journals in China. Both the number of literature and the reference frequency were very low. CONCLUSION In the treatment and prevention of tuberculosis, the collection of the best evidence is particularly important. There is a certain gap on this research between China and abroad. China, as a TB high burden country, not only should increase the number of literature, but also ensure the quality of literature.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics, Insufficient payload (model declined to judge)
Consensus categoriesBibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.634
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0350.066
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 head0.033
GPT teacher head0.356
Teacher spread0.323 · 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

Labeled directly by 2 models reading the full record.

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

Citations0
Published2013
Admission routes1
Has abstractyes

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