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Record W1568789937 · doi:10.1002/asi.23166

The kiss of death? The effect of being cited in a review on subsequent citations

2014· review· en· W1568789937 on OpenAlexaff
Christian Lachance, Steve Poirier, Vincent Larivière

Bibliographic record

VenueJournal of the Association for Information Science and Technology · 2014
Typereview
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsUniversité du Québec à MontréalMontreal Heart InstituteUniversité de Montréal
Fundersnot available
KeywordsCitationKISS (TNC)Science Citation IndexSpecialtyField (mathematics)Citation analysisComputer scienceMedicineLibrary scienceFamily medicineMathematics

Abstract

fetched live from OpenAlex

This work investigates recent claims that citation in a review article provokes a decline in a paper's later citation count; citations being given to the review article instead of the original paper. Using the Science Citation Index Expanded , we looked at the yearly percentages of lifetime citations of papers published in 1990 first cited in review articles in 1992 and 1995 in the field of biomedical research, and found that no significant change occurred after citation in a review article, regardless of the papers' citation activity or specialty. Additional comparison was done for papers from the field of clinical research, and this yielded no meaningful results to support the notion that review articles have any substantial effect on the citation count of the papers they review.

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)0.102
metaresearch head score (Gemma)0.257
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesMetaresearch, Bibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1020.257
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0230.104
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0030.000
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 head0.239
GPT teacher head0.548
Teacher spread0.309 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations16
Published2014
Admission routes1
Has abstractyes

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