Issue/79/refactoring partial

docs/desc-0000-qp-photo-z_approximation/main.bib

@@ -407,7 +407,6 @@ @article{radovich_searching_2017
 @article{de_jong_third_2017,
 	title = {The third data release of the {Kilo}-{Degree} {Survey} and associated data products},
 	volume = {604},
-	url = {https://ui.adsabs.harvard.edu/#abs/2017A&A...604A.134D/abstract},
 	doi = {10.1051/0004-6361/201730747},
 	journal = {Astronomy and Astrophysics},
 	author = {de Jong, A. Jelte T. and A, Jelte T. and Kleijn, Gijs A. Verdoes and Erben, Thomas and Hildebrandt, Hendrik and Kuijken, Konrad and Sikkema, Gert and Brescia, Massimo and Bilicki, Maciej and Napolitano, Nicola R. and Amaro, Valeria and Begeman, Kor G. and Boxhoorn, Danny R. and Buddelmeijer, Hugo and Cavuoti, Stefano and Getman, Fedor and Grado, Aniello and Helmich, Ewout and Huang, Zhuoyi and Irisarri, Nancy and La Barbera, Francesco and Longo, Giuseppe and McFarland, John P. and Nakajima, Reiko and Paolillo, Maurizio and Puddu, Emanuella and Radovich, Mario and Rifatto, Agatino and Tortora, Crescenzo and Valentijn, Edwin A. and Vellucci, Civita and Vriend, Willem-Jan and Amon, Alexandra and Blake, Chris and Choi, Ami and Conti, Ian Fenech and Gwyn, Stephen D. J. and Herbonnet, Ricardo and Heymans, Catherine and Hoekstra, Henk and Klaes, Dominik and Merten, Julian and Miller, Lance and Schneider, Peter and Viola, Massimo},

docs/desc-0000-qp-photo-z_approximation/main.tex

@@ -465,7 +465,7 @@ \subsection{Comparison Metrics}
 of a PDF.
 We note that $M_{0}[P]=1$ for all properly normalized probability 
 distributions, $M_{1}[P]=\bar{z}$ is the \textit{mean}, $M_{2}[P]$ is the 
-\textit{variance}, and $M_{3}[P]$ is the \textit{kurtosis}.
+\textit{variance}, and $M_{3}[P]$ is the \textit{skewness}.
 Though the first few moments are not in general sufficient to characterize a 
 highly structured probability distribution, they are included in this analysis 
 because they can prove useful in setting ballpark estimates of the influence of 
@@ -705,7 +705,7 @@ \subsection{Individual \pz s}
     \includegraphics[width=\columnwidth]{graham_pz_kld.pdf}
     \includegraphics[width=\columnwidth]{schmidt_pz_kld.pdf}
     \caption{
-    The means of the mean ($\pentagon$), variance ($\bigstar$), and kurtosis 
+    The means of the mean ($\pentagon$), variance ($\bigstar$), and skewness 
 ($\APLstar$) of the log-KLD distributions for each dataset as a function of the 
 number $N_{f}$ of stored parameters for the quantile (dashed purple line), 
 samples (dash-dotted green line), and histogram (dotted orange line) formats 
@@ -762,7 +762,7 @@ \subsection{Individual \pz s}
     \includegraphics[width=\columnwidth]{schmidt_pz_err.pdf}
     \caption{
    The median $\log_{10}$-percent errors on the mean ($\pentagon$), variance 
-($\bigstar$), and kurtosis ($\APLstar$) of the \pz s for each dataset as a 
+($\bigstar$), and skewness ($\APLstar$) of the \pz s for each dataset as a 
 function of the number $N_{f}$ of stored parameters per \pz\ for the quantile 
 (dashed purple line), samples (dash-dotted green line), and histogram (dotted 
 orange line) formats with interquartile range error bars based on 10 
@@ -952,7 +952,7 @@ \subsection{Stacked $\hat{n}(z)$ estimator}
 \includegraphics[width=\columnwidth]{schmidt_nz_err.pdf}
     \caption{
     The percent error on the mean ($\pentagon$), variance ($\bigstar$), and 
-kurtosis ($\APLstar$) of the stacked estimator $hat{n}(z)$ of the redshift 
+skewness ($\APLstar$) of the stacked estimator $hat{n}(z)$ of the redshift 
 distribution for each dataset as a function of the number $N_{f}$ of stored 
 parameters for the quantile (dashed purple line), samples (dash-dotted 
 greenline), and histogram (dotted orangeline) formats with interquartile range 
@@ -1194,6 +1194,7 @@ \subsection*{Acknowledgments}
 \input{acknowledgments}
 
 
+
 \bibliography{lsstdesc,main}
 
 \end{document}