Remove 'Figure X' from caption - automatically populated in journal draft

Author: RhysPeploe

paper/paper.md

@@ -134,7 +134,7 @@ A key limitation is that the `iddoverse` functions cannot address every need of
 in the datasets within, and across, diseases. The objective has been to provide assistance and automation of analysis
 datasets, whilst keeping the solution generalisable and customisable by the user. 
 
-![Figure 1: Flowchart of functions within the `iddoverse` package.](figures/Figure 1 - Function Flowchart.tif)
+![Flowchart of functions within the `iddoverse` package.](figures/Figure 1 - Function Flowchart.tif)
 
 # iddoverse Functions
 
@@ -149,7 +149,7 @@ diseases and will not be relevant to most. The hierarchy of timing variables is
 parameter to enable researchers to select the most appropriate variable(s) for their analysis. By choosing a ‘best choice’ timing 
 and result, potential confusion surrounding multiple columns is removed. 
 
-![Figure 2: Hierarchy of best choice results/events/findings in `prepare_domain()`. `STRESN` or `DECOD` would be used in the first instance and, where rows are missing this information, they are populated with the variables under them in order. The two letter domain code preceeds these variable names.](figures/Figure 2 - Hierarchy Choices.tif)
+![Hierarchy of best choice results/events/findings in `prepare_domain()`. `STRESN` or `DECOD` would be used in the first instance and, where rows are missing this information, they are populated with the variables under them in order. The two letter domain code preceeds these variable names.](figures/Figure 2 - Hierarchy Choices.tif)
 
 The `prepare_domain()` function then pivots the rows by the best choice time variable (`TIME`, `TIME_SOURCE`), the study ID (`STUDYID`) 
 and participant number (`USUBJID`). The different events/findings/tests are transformed into columns, and the dataset is populated