A reverse engineering approach to the suppression of citation biases reveals universal properties of citation distributions

The large amount of information contained in bibliographic databases has recently boosted the use of citations, and other indicators based on citation numbers, as tools for the quantitative assessment of scientific research. Citations counts are often interpreted as proxies for the scientific influence of papers, journals, scholars, and institutions. However, a rigorous and scientifically grounded methodology for a correct use of citation counts is still missing. In particular, cross-disciplinary comparisons in terms of raw citation counts systematically favors scientific disciplines with higher citation and publication rates. Here we perform an exhaustive study of the citation patterns of millions of papers, and derive a simple transformation of citation counts able to suppress the disproportionate citation counts among scientific domains. We find that the transformation is well described by a power-law function, and that the parameter values of the transformation are typical features of each scientific discipline. Universal properties of citation patterns descend therefore from the fact that citation distributions for papers in a specific field are all part of the same family of univariate distributions.Comment: 9 pages, 6 figures. Supporting information files available at http://filrad.homelinux.or

Assessing the impact of biomedical research in academic institutions of disparate sizes

Abstract Background The evaluation of academic research performance is nowadays a priority issue. Bibliometric indicators such as the number of publications, total citation counts and h-index are an indispensable tool in this task but their inherent association with the size of the research output may result in rewarding high production when evaluating institutions of disparate sizes. The aim of this study is to propose an indicator that may facilitate the comparison of institutions of disparate sizes. Methods The Modified Impact Index (MII) was defined as the ratio of the observed h-index (h) of an institution over the h-index anticipated for that institution on average, given the number of publications (N) it produces i.e. (α and β denote the intercept and the slope, respectively, of the line describing the dependence of the h-index on the number of publications in log10 scale). MII values higher than 1 indicate that an institution performs better than the average, in terms of its h-index. Data on scientific papers published during 2002–2006 and within 36 medical fields for 219 Academic Medical Institutions from 16 European countries were used to estimate α and β and to calculate the MII of their total and field-specific production. Results From our biomedical research data, the slope β governing the dependence of h-index on the number of publications in biomedical research was found to be similar to that estimated in other disciplines (≈0.4). The MII was positively associated with the average number of citations/publication (r = 0.653, p Conclusion The MII should complement the use of h-index when comparing the research output of institutions of disparate sizes. It has a conceptual interpretation and, with the data provided here, can be computed for the total research output as well as for field-specific publication sets of institutions in biomedicine.</p

Worldwide topology of the scientific subject profile: a macro approach in the country level

[Background] Models for the production of knowledge and systems of innovation and science are key elements for characterizing a country in view of its scientific thematic profile. With regard to scientific output and publication in journals of international visibility, the countries of the world may be classified into three main groups according to their thematic bias.[Methodology/Principal Findings] This paper aims to classify the countries of the world in several broad groups, described in terms of behavioural models that attempt to sum up the characteristics of their systems of knowledge and innovation. We perceive three clusters in our analysis: 1) the biomedical cluster, 2) the basic science & engineering cluster, and 3) the agricultural cluster. The countries are conceptually associated with the clusters via Principal Component Analysis (PCA), and a Multidimensional Scaling (MDS) map with all the countries is presented.[Conclusions/Significance] As we have seen, insofar as scientific output and publication in journals of international visibility is concerned, the countries of the world may be classified into three main groups according to their thematic profile. These groups can be described in terms of behavioral models that attempt to sum up the characteristics of their systems of knowledge and innovation

Lateral frontal cortex volume reduction in Tourette syndrome revealed by VBM

<p>Abstract</p> <p>Background</p> <p>Structural changes have been found predominantly in the frontal cortex and in the striatum in children and adolescents with Gilles de la Tourette syndrome (GTS). The influence of comorbid symptomatology is unclear. Here we sought to address the question of gray matter abnormalities in GTS patients <it>with </it>co-morbid obsessive-compulsive disorder (OCD) and/or attention deficit hyperactivity disorder (ADHD) using voxel-based morphometry (VBM) in twenty-nine adult actually unmedicated GTS patients and twenty-five healthy control subjects.</p> <p>Results</p> <p>In GTS we detected a cluster of decreased gray matter volume in the left inferior frontal gyrus (IFG), but no regions demonstrating volume increases. By comparing subgroups of GTS with comorbid ADHD to the subgroup with comorbid OCD, we found a left-sided amygdalar volume increase.</p> <p>Conclusions</p> <p>From our results it is suggested that the left IFG may constitute a common underlying structural correlate of GTS with co-morbid OCD/ADHD. A volume reduction in this brain region that has been previously identified as a key region in OCD and was associated with the active inhibition of attentional processes may reflect the failure to control behavior. Amygdala volume increase is discussed on the background of a linkage of this structure with ADHD symptomatology. Correlations with clinical data revealed gray matter volume changes in specific brain areas that have been described in these conditions each.</p