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Record W2385673000

Bibliometric analysis of systematic review on tuberculosis literature in Web of science

2011· article· en· W2385673000 on OpenAlexaboutno aff
Jing Lv

Bibliographic record

VenueChinese Journal of Disease Control and Prevention · 2011
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Vectors
Canadian institutionsnot available
Fundersnot available
KeywordsTuberculosisWeb of scienceSystematic reviewCitationScience Citation IndexMedicineBibliometricsCitation analysisMEDLINEOriginal researchFamily medicineMeta-analysisPolitical scienceLibrary sciencePathologyComputer science
DOInot available

Abstract

fetched live from OpenAlex

Objective To understand the progress in systematic review on tuberculosis over the last 10 years through a bibliometric approach. Methods Literatures about systematic review on tuberculosis(2001-2010) were searched from the ISI Web of science citation database.The searching results were analyzed concerning the article numbers and the frequency of citation by countries,institutions and authors,periodical distribution,and study areas distribution.Results Overall 232 papers from 110 types of journals were found.The number of papers had increased significantly over the last five years.The developed country,just as USA,Canada and United Kingdom have played important roles in the systematic review on tuberculosis research in the world.The systematic review on tuberculosis subject areas focused on infectious diseases,respiratory diseases,medicine(general internal),public health,microbiology,immunology,and so on.Conclusions In the prevention and control of tuberculosis,the best evidence has attracted more and more attention.As a tuberculosis high burden country,China should improve the level of investment and research on systematic review on tuberculosis.

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
Other designhigh
models splitAgreement 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesBibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0310.057
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.314
Teacher spread0.296 · 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.

Bibliometrics

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Other design
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
Published2011
Admission routes1
Has abstractyes

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