I study the measurement of the influence of scientists based on bibliographic data. I propose a new measure that accounts for indirect influence and allows to compare scientists across different fields of science. By contrast, common measures of influence that “count citations”, such as the h-index, are unable to satisfy either of these two properties. I use the axiomatic method in two opposite ways: to highlight the two limitations of citation-counting schemes and their independence, and to carefully justify the assumptions made in the construction of the proposed measure.

 

Measuring Influence in Science: Standing on the Shoulders of Which Giants?
Antonin Macé

Source: arxiv.org

Mutualistic interactions, which are beneficial for both interacting species, are recurrently present in ecosystems. Observations of natural systems showed that, if we draw mutualistic relationships as binary links between species, the resulting bipartite network of interactions displays a widespread particular ordering called nestedness. On the other hand, theoretical works have shown that a nested structure has a positive impact on a number of relevant features ranging from species coexistence to a higher structural stability of communities and biodiversity. However, how nestedness emerges and what are its determinants, are still open challenges that have led to multiple debates to date. Here, we show, by applying a theoretical approach to the analysis of 167 real mutualistic networks, that nestedness is not an irreducible feature, but a consequence of the degree sequences of both guilds of the mutualistic network. Remarkably, we find that an outstanding majority of the analyzed networks does not show statistical significant nestedness. These findings point to the need of revising previous claims about the role of nestedness and might contribute to expanding our understanding of how evolution shapes mutualistic interactions and communities by placing the focus on the local properties rather than on global quantities.

 

Breaking the spell of nestedness
Claudia Payrato Borras, Laura Hernandez, Yamir Moreno
doi: https://doi.org/10.1101/216564

Source: www.biorxiv.org

In this paper we explore several fundamental relations between formal systems, algorithms, and dynamical systems, focussing on the roles of undecidability, universality, diagonalization, and self-reference in each of these computational frameworks. Some of these interconnections are well-known, while some are clarified in this study as a result of a fine-grained comparison between recursive formal systems, Turing machines, and Cellular Automata (CAs). In particular, we elaborate on the diagonalization argument applied to distributed computation carried out by CAs, illustrating the key elements of G\”odel’s proof for CAs. The comparative analysis emphasizes three factors which underlie the capacity to generate undecidable dynamics within the examined computational frameworks: (i) the program-data duality; (ii) the potential to access an infinite computational medium; and (iii) the ability to implement negation. The considered adaptations of G\”odel’s proof distinguish between computational universality and undecidability, and show how the diagonalization argument exploits, on several levels, the self-referential basis of undecidability.

 

Self-referential basis of undecidable dynamics: from The Liar Paradox and The Halting Problem to The Edge of Chaos
Mikhail Prokopenko, Michael Harré, Joseph Lizier, Fabio Boschetti, Pavlos Peppas, Stuart Kauffman

Source: arxiv.org

Machines seem to be getting smarter and smarter and much better at human jobs, yet true AI is utterly implausible. Why?

Source: aeon.co