Evidence map›Paper›PMID 23720314›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2013

Determining scientific impact using a collaboration index.

Jonathan Stallings, Eric Vance, Jiansheng Yang, Michael W Vannier, Jimin Liang, Liaojun Pang, Liang Dai, Ivan Ye, Ge Wang

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Bibliometric Analysis of 6 Major European Neurosurgical Publications from 2011-2020 (part 3): a Comparative Metrics Review.Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH · 2023
    Article
  4. Review
  5. Article
  6. Article
  7. Evaluating Journal Impact Factor: a systematic survey of the pros and cons, and overview of alternative measures.The journal of venomous animals and toxins including tropical diseases · 2020
    Article
  8. Article
  9. Article
  10. Two New Factors for the Evaluation of Scientific Performance:Turkish journal of pharmaceutical sciences · 2019
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. A Discussion on Governmental Research Grants.Science and engineering ethics · 2015
    Article
  17. Quantifying the impact of weak, strong, and super ties in scientific careers.Proceedings of the National Academy of Sciences of the United States of America · 2015
    Article
  18. Article
  19. Collective credit allocation in science.Proceedings of the National Academy of Sciences of the United States of America · 2014
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Jonathan StallingsDepartment of Statistics, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA.
Eric Vance
Jiansheng Yang
Michael W Vannier
Jimin Liang
Liaojun Pang
Liang Dai
Ivan Ye
Ge Wang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Researchers collaborate on scientific projects that are often measured by both the quantity and the quality of the resultant peer-reviewed publications. However, not all collaborators contribute to these publications equally, making metrics such as the total number of publications and the H-index insufficient measurements of individual scientific impact. To remedy this, we use an axiomatic approach to assign relative credits to the coauthors of a given paper, referred to as the A-index for its axiomatic foundation. In this paper, we use the A-index to compute the weighted sums of peer-reviewed publications and journal impact factors, denoted as the C- and P-indexes for collaboration and productivity, respectively. We perform an in-depth analysis of bibliometric data for 186 biomedical engineering faculty members and from extensive simulation. It is found that these axiomatically weighted indexes better capture a researcher's scientific caliber than do the total number of publications and the H-index, allowing for fairer and sharper evaluation of researchers with diverse collaborative behaviors.

Indexed as

BibliometricsJournal Impact FactorAuthorshipBiomedical ResearchCooperative BehaviorEfficiencyHumansMonte Carlo MethodPeer Review, ResearchPeriodicals as TopicResearch Personnel

Identifiers

PMID23720314
PMCPMC3683734

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.