Evidence map›Paper›PMID 25046832›Full record

ArticleJournal of biomedical informatics2014

Associating co-authorship patterns with publications in high-impact journals.

Michael E Bales, Daniel C Dine, Jacqueline A Merrill, Stephen B Johnson, Suzanne Bakken, Chunhua Weng

Abstract read
In one paragraph

Article in Journal of biomedical informatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Games academics play and their consequences: how authorship,Proceedings. Biological sciences · 2019
    Article
  5. Article
  6. Article
  7. Article
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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

6 authors.

Michael E BalesDepartment of Biomedical Informatics, Columbia University, New York City, United States; The Irving Institute for Clinical and Translational Research, Columbia University, New York City, United States.
Daniel C DineThe Irving Institute for Clinical and Translational Research, Columbia University, New York City, United States.
Jacqueline A MerrillDepartment of Biomedical Informatics, Columbia University, New York City, United States; School of Nursing, Columbia University, New York City, United States.
Stephen B JohnsonWeill Cornell Medical College, New York City, United States.
Suzanne BakkenDepartment of Biomedical Informatics, Columbia University, New York City, United States; The Irving Institute for Clinical and Translational Research, Columbia University, New York City, United States; School of Nursing, Columbia University, New York City, United States.
Chunhua WengDepartment of Biomedical Informatics, Columbia University, New York City, United States; The Irving Institute for Clinical and Translational Research, Columbia University, New York City, United States. Electronic address: cw2384@columbia.edu.

Funding

Clinical and Translational Science AwardUL1TR000040 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GINSBERG, HENRY N · 2012 to 2015
$26.2M
Bridging the Semantic Gap Between Research Eligibility Criteria and Clinical DataR01LM009886 · NLM · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI WENG, CHUNHUA · 2009 to 2020
$5.3M
NCATS NIH HHS UL1 TR000040NLM NIH HHS R01 LM009886
6 · The paper itself

Abstract

objectivesTo develop a method for investigating co-authorship patterns and author team characteristics associated with the publications in high-impact journals through the integration of public MEDLINE data and institutional scientific profile data.

methodsFor all current researchers at Columbia University Medical Center, we extracted their publications from MEDLINE authored between years 2007 and 2011 and associated journal impact factors, along with author academic ranks and departmental affiliations obtained from Columbia University Scientific Profiles (CUSP). Chi-square tests were performed on co-authorship patterns, with Bonferroni correction for multiple comparisons, to identify team composition characteristics associated with publication impact factors. We also developed co-authorship networks for the 25 most prolific departments between years 2002 and 2011 and counted the internal and external authors, inter-connectivity, and centrality of each department.

resultsPapers with at least one author from a basic science department are significantly more likely to appear in high-impact journals than papers authored by those from clinical departments alone. Inclusion of at least one professor on the author list is strongly associated with publication in high-impact journals, as is inclusion of at least one research scientist. Departmental and disciplinary differences in the ratios of within- to outside-department collaboration and overall network cohesion are also observed.

conclusionsEnrichment of co-authorship patterns with author scientific profiles helps uncover associations between author team characteristics and appearance in high-impact journals. These results may offer implications for mentoring junior biomedical researchers to publish on high-impact journals, as well as for evaluating academic progress across disciplines in modern academic medical centers.

Indexed as

AuthorshipJournal Impact FactorBiomedical ResearchHumansMEDLINENew York CityPublicationsUniversitiesCo-authorship patternsEvaluationJournal impact factorMEDLINESocial networking

Identifiers

PMID25046832
PMCPMC4260991

What OpenQuestion holds

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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.