Fix citations

paper/paper.bib

@@ -97,7 +97,7 @@ @misc{Ward2017
 }
 
 @book{IPCC2014,
- title = {Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change},
+ title = {Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group {III} to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change},
  author = {IPCC},
  editor = {Edenhofer, O. and Pichs-Madruga, R. and Sokona, Y. and Farahani, E. and Kadner, S. and Seyboth, K. and Adler, A. and Baum, I. and Brunner, S. and Eickemeier, P. and Kriemann, B. and Savolainen, J. and Schlömer, S. and von Stechow, C. and Zwickel, T. and Minx, J.C.},
  year = {2014},

paper/paper.md

@@ -29,7 +29,7 @@ output: pdf_document
 Pymagicc is a Python wrapper for the Fortran-based reduced-complexity climate carbon cycle model MAGICC [@Meinshausen2011].
 Aiming at broadening the user base of MAGICC^[http://magicc.org], Pymagicc provides a wrapper around the MAGICC binary^[http://magicc.org/download6], which runs on Windows and has been published under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License^[https://creativecommons.org/licenses/by-nc-sa/3.0/].
 Pymagicc runs on Windows, macOS and Linux and simplifies usage of the model by utilising DataFrames from the Pandas library [@McKinney2010] as a data structure for emissions scenarios.
-To read and write the text-based MAGICC configuration and output files in the Fortran Namelist format Pymagicc utilizes the f90nml [@Ward2017] library.
+To read and write the text-based MAGICC configuration and output files in the Fortran Namelist format Pymagicc utilizes the f90nml library [@Ward2017].
 All MAGICC model parameters and emissions scenarios can thus easily be modified through Pymagicc from Python.
 
 MAGICC (Model for the Assessment of Greenhouse Gas Induced Climate Change)