@article{MTMT:31397251, title = {Research funding: past performance is a stronger predictor of future scientific output than reviewer scores}, url = {https://m2.mtmt.hu/api/publication/31397251}, author = {Győrffy, Balázs and Herman, P.E. and Szabó, István}, doi = {10.1016/j.joi.2020.101050}, journal-iso = {J INFORMETRICS}, journal = {JOURNAL OF INFORMETRICS}, volume = {14}, unique-id = {31397251}, issn = {1751-1577}, abstract = {Scientific grants are awarded almost exclusively on the basis of an independent peer review of a proposal submitted by the principal investigator (PI). The writing and reviewing of these applications consumes a significant amount of researchers' time. Here, we perform a large-scale performance evaluation of review-based grant allocation via analysis of the grant proposals submitted to the Hungarian Scientific Research Fund. In total, 42,905 scored review reports prepared for 13,303 proposals submitted between 2006 and 2015 were analyzed. The publication and citation characteristics of the PIs were obtained from the Hungarian Scientific Work Archive (www.mtmt.hu). Each publication was assigned to its respective SCImago Journal Rank category, and only publications in the first quarter (Q1) were considered. Citation, H-index and publication data were derived for each analyzed year for each researcher. Of all proposals, 3455 were funded (26%). PIs with a funded proposal had significantly more Q1 articles and first/last authored Q1 articles (1.91 vs. 1.30, p<1e-16 and 0.82 vs 0.53, p<1e-16, respectively). Of the successful applications, those involving international collaborations and extended budget had higher publication output. Applicant age, grant duration, and submission year were not correlated with publication performance. Reviewer scores displayed a minor association (corr.coeff = 0.08-011) with the number of Q1 publications. International reviewers were significantly less efficient than national reviewers (p = 0.021). A strong correlation with output was observed for the scientometric characteristics of the applying PI at the time of submission, including H-index (corr.coeff = 0.45-0.54), independent citation (corr.coeff. = 0.46-0.62), and yearly average Q1 articles (corr.coeff = 0.63-0.79, p<1e-16). Similar correlations were observed for nonfunded applicants. We performed a comprehensive evaluation of review-based resource allocation efficiency in basic research funding. Evidence suggests that the past scientometric performance of the principal investigator is the best predictor of future output. © 2020 The Authors.}, keywords = {PUBLICATIONS; h-index; publishing; Strong correlation; funding; Scientific researches; Indexing (of information); Comprehensive evaluation; Basic research; Budget control; internationalization; International collaborations; Scientific output; Scientific output; Principal investigators; Q1; Reviewer assessments; Allocation efficiencies; Independent peer reviews}, year = {2020}, eissn = {1875-5879}, orcid-numbers = {Győrffy, Balázs/0000-0002-5772-3766} } @article{MTMT:31346056, title = {Is there a golden age in publication activity?—an analysis of age-related scholarly performance across all scientific disciplines}, url = {https://m2.mtmt.hu/api/publication/31346056}, author = {Győrffy, Balázs and Csuka, Gyöngyi and Herman, Péter and Török, Ádám}, doi = {10.1007/s11192-020-03501-w}, journal-iso = {SCIENTOMETRICS}, journal = {SCIENTOMETRICS}, volume = {124}, unique-id = {31346056}, issn = {0138-9130}, abstract = {We examined whether the publication characteristics of various scientific disciplines exhibit age-related trends. Our analysis was based on two large data sets comprising all major scientific disciplines. Citation data for European Research Council grant holders (ERC, n = 756) were obtained from Google Scholar. Publication data for Hungarian researchers (HUN, n = 2469) were obtained from the Hungarian Scientific Work Archive. The evaluated performance parameters include the number of citations received and the number of high quality first/last author papers published in the last five years. We designated the time between maximum growth and the achieved maximal annual value of total citations as the Golden Age of a researcher. Regarding citation growth, the mean age at the highest growth was 41.75 and 41.53 years for ERC grantees and Hungarian researchers, respectively. Each discipline had different values, with mathematics (38.5 years, ERC) and biology (34.7 years, HUN) having the youngest mean age of highest citation growth and agriculture (45.2 years, ERC) and language sciences (49.9 years, HUN) having the oldest mean age. The maximal growth of publications occurred at 44.5 years, with physics starting first (40.5 years, HUN) and language sciences as last (51.4 years, HUN). Most academic careers require decades to reach their peak and the length of the period of maximum performance varies across disciplines. The most creative time period is rising and is currently in the second half of the forties. Identifying the Golden Age in diverse research careers may be of substantial help in the distribution of grants and tenure positions.}, keywords = {CITATION; Scientific discipline; ERC; Science performance}, year = {2020}, eissn = {1588-2861}, pages = {1081-1097}, orcid-numbers = {Győrffy, Balázs/0000-0002-5772-3766; Török, Ádám/0000-0001-9062-2011} } @{MTMT:35025734, title = {A Magyar Tudományos Művek Tára (MTMT) MyCite2 szoftvere}, url = {https://m2.mtmt.hu/api/publication/35025734}, unique-id = {35025734}, keywords = {MTMT}, year = {2018} } @article{MTMT:3399002, title = {Factors influencing the scientific performance of Momentum grant holders: an evaluation of the first 117 research groups}, url = {https://m2.mtmt.hu/api/publication/3399002}, author = {Győrffy, Balázs and Nagy, Andrea Magda and Herman, Péter and Török, Ádám}, doi = {10.1007/s11192-018-2852-1}, journal-iso = {SCIENTOMETRICS}, journal = {SCIENTOMETRICS}, volume = {117}, unique-id = {3399002}, issn = {0138-9130}, year = {2018}, eissn = {1588-2861}, pages = {409-426}, orcid-numbers = {Győrffy, Balázs/0000-0002-5772-3766; Nagy, Andrea Magda/0000-0003-1492-4362; Török, Ádám/0000-0001-9062-2011} }