CEXS-UPF: PIPredictor: a mathematical model that predicts how successful researchers will be

CEXS-UPF: PIPredictor: a mathematical model that predicts how successful researchers will be

News from CEXS-UPF

An international group of researchers has developed a mathematical model based on a large database of scientific publications: PIPredictor, which is able to predict who will become a principal investigator. This predictive model is available online for anyone who is interested in knowing what the future holds:

The study was published on 2 June, 2014 in the journalCurrent Biology and was directed by Lucas Carey, principal investigator at the Single Cell Behavior Lab at the Department of Experimental and Health Sciences (UPF), with Ohad Manor (University of Washington, USA) and David van Dijk (Weissman Institute, Israel).

Just from the record of publications, the authors have been able to predict with high accuracy who will become a principal investigator and when. This prediction is merely informative and suggests that other factors such as personal contacts and social skills may be important and correlated with the scientific promotion.

Furthermore, the study also shows that the prestige of the journal is much more important than the number of times a work is cited by others, i.e. the perceived quality exceeds the actual scientific quality.

The mathematical model was developed to measure the effect of the researcher's gender on his/her scientific career and the prestige of the university where s/he studied. It shows that men from high ranking universities not only have the best curriculum, but also that they are more likely to become principal investigators than females under conditions of equal curricula.

David van Dijk, Ohad Manor, Lucas B. Carey (2014) "A quantitative analysis of publication metrics and success on the academic job market" Current Biology, vol. 24, no. 11.

More information:
CEXS-UPF website