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Record W1516312676

Highly Cited Canada Articles in Science Citation Index Expanded: A Bibliometric Analysis

2015· article· en· W1516312676 on OpenAlexvenueaboutno aff
Hui‐Zhen Fu, Yuh‐Shan Ho

Bibliographic record

VenueCanadian social science · 2015
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsnot available
Fundersnot available
KeywordsCitationScience Citation IndexLibrary scienceIndex (typography)Web of scienceBibliometricsCitation analysisInstitutionMultidisciplinary approachPolitical scienceSocial scienceSociologyComputer scienceMEDLINEWorld Wide WebLaw
DOInot available

Abstract

fetched live from OpenAlex

The characteristics of the highly cited Canada articles in Science Citation Index Expanded from 1900 to 2011 were revealed. Articles that have been cited at least 100 times since publication to 2011 were assessed regarding their distribution in indexed journals and categories of the Web of Science. The citation lives of the top articles depending on citations in publication year, recent year, and years after publications were investigated for the impact history of articles. A new indicator, Y-index, was successfully applied to evaluate publication characteristics of Canada authors and institutions. University of Toronto was the most productive institution. The top three most productive categories of the Web of Science were biochemistry and molecular biology, multidisciplinary sciences, and neurosciences. Journal of Biological Chemistry and Nature hosted the most highly cited Canada articles. In addition, the Y-index was applied to evaluate the publication character of authors and institutions.

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: yes
Observationallow
gptBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: yes
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)0.043
metaresearch head score (Gemma)0.069
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Scholarly communication
Consensus categoriesMetaresearch, Bibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.166
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0430.069
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.8140.980
Science and technology studies0.0010.002
Scholarly communication0.0050.002
Open science0.0050.000
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 head0.400
GPT teacher head0.505
Teacher spread0.104 · 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

Citations14
Published2015
Admission routes2
Has abstractyes

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