diff --git a/README.md b/README.md
index 52f57dcfb..8f532c320 100644
--- a/README.md
+++ b/README.md
@@ -167,17 +167,21 @@ example_quantile %>%
 #> Some rows containing NA values may be removed. This is fine if not unexpected.
 #> Some rows containing NA values may be removed. This is fine if not unexpected.
 #> Some rows containing NA values may be removed. This is fine if not unexpected.
+#> Warning in get_score_names(scores, error = TRUE): The following scores have
+#> been previously computed, but are no longer column names of the data:
+#> `interval_coverage, quantile_coverage, quantile_coverage_deviation`. See
+#> `?get_score_names` for further information.
 ```
 
-| model                 | target_type |   wis | overprediction | underprediction | dispersion |    bias | interval_coverage_50 | interval_coverage_90 | interval_coverage_deviation | ae_median | relative_skill | scaled_rel_skill |
-|:----------------------|:------------|------:|---------------:|----------------:|-----------:|--------:|---------------------:|---------------------:|----------------------------:|----------:|---------------:|-----------------:|
-| EuroCOVIDhub-baseline | Cases       | 28000 |        14000.0 |         10000.0 |       4100 |  0.0980 |                 0.33 |                 0.82 |                      -0.120 |     38000 |           1.30 |              1.6 |
-| EuroCOVIDhub-baseline | Deaths      |   160 |           66.0 |             2.1 |         91 |  0.3400 |                 0.66 |                 1.00 |                       0.120 |       230 |           2.30 |              3.8 |
-| EuroCOVIDhub-ensemble | Cases       | 18000 |        10000.0 |          4200.0 |       3700 | -0.0560 |                 0.39 |                 0.80 |                      -0.100 |     24000 |           0.82 |              1.0 |
-| EuroCOVIDhub-ensemble | Deaths      |    41 |            7.1 |             4.1 |         30 |  0.0730 |                 0.88 |                 1.00 |                       0.200 |        53 |           0.60 |              1.0 |
-| UMass-MechBayes       | Deaths      |    53 |            9.0 |            17.0 |         27 | -0.0220 |                 0.46 |                 0.88 |                      -0.025 |        78 |           0.75 |              1.3 |
-| epiforecasts-EpiNow2  | Cases       | 21000 |        12000.0 |          3300.0 |       5700 | -0.0790 |                 0.47 |                 0.79 |                      -0.070 |     28000 |           0.95 |              1.2 |
-| epiforecasts-EpiNow2  | Deaths      |    67 |           19.0 |            16.0 |         32 | -0.0051 |                 0.42 |                 0.91 |                      -0.045 |       100 |           0.98 |              1.6 |
+| model                 | target_type |   wis | overprediction | underprediction | dispersion |    bias | interval_coverage_50 | interval_coverage_90 | interval_coverage_deviation | ae_median | wis_relative_skill | wis_scaled_relative_skill |
+|:----------------------|:------------|------:|---------------:|----------------:|-----------:|--------:|---------------------:|---------------------:|----------------------------:|----------:|-------------------:|--------------------------:|
+| EuroCOVIDhub-baseline | Cases       | 28000 |        14000.0 |         10000.0 |       4100 |  0.0980 |                 0.33 |                 0.82 |                      -0.120 |     38000 |               1.30 |                       1.6 |
+| EuroCOVIDhub-baseline | Deaths      |   160 |           66.0 |             2.1 |         91 |  0.3400 |                 0.66 |                 1.00 |                       0.120 |       230 |               2.30 |                       3.8 |
+| EuroCOVIDhub-ensemble | Cases       | 18000 |        10000.0 |          4200.0 |       3700 | -0.0560 |                 0.39 |                 0.80 |                      -0.100 |     24000 |               0.82 |                       1.0 |
+| EuroCOVIDhub-ensemble | Deaths      |    41 |            7.1 |             4.1 |         30 |  0.0730 |                 0.88 |                 1.00 |                       0.200 |        53 |               0.60 |                       1.0 |
+| UMass-MechBayes       | Deaths      |    53 |            9.0 |            17.0 |         27 | -0.0220 |                 0.46 |                 0.88 |                      -0.025 |        78 |               0.75 |                       1.3 |
+| epiforecasts-EpiNow2  | Cases       | 21000 |        12000.0 |          3300.0 |       5700 | -0.0790 |                 0.47 |                 0.79 |                      -0.070 |     28000 |               0.95 |                       1.2 |
+| epiforecasts-EpiNow2  | Deaths      |    67 |           19.0 |            16.0 |         32 | -0.0051 |                 0.42 |                 0.91 |                      -0.045 |       100 |               0.98 |                       1.6 |
 
 `scoringutils` contains additional functionality to transform forecasts,
 to summarise scores at different levels, to visualise them, and to
@@ -200,6 +204,7 @@ example_quantile %>%
   summarise_scores(by = c("model", "target_type", "scale")) %>%
   head()
 #> Some rows containing NA values may be removed. This is fine if not unexpected.
+#> Some rows containing NA values may be removed. This is fine if not unexpected.
 #>                    model target_type   scale         wis overprediction
 #> 1: EuroCOVIDhub-ensemble       Cases natural 11550.70664    3650.004755
 #> 2: EuroCOVIDhub-baseline       Cases natural 22090.45747    7702.983696