diff --git a/R/MeasureSurvRCLL.R b/R/MeasureSurvRCLL.R
index 471496f45..613551c2d 100644
--- a/R/MeasureSurvRCLL.R
+++ b/R/MeasureSurvRCLL.R
@@ -16,6 +16,10 @@
 #' density function and \eqn{S} the survival function.
 #' RCLL is proper given that censoring and survival distribution are independent, see Rindt et al. (2022).
 #'
+#' **Note**: Even though RCLL is a proper scoring rule, the calculation of \eqn{f(t)} (which in our case is discrete, i.e. it is a *probability mass function*) for time points in the test set that don't exist in the predicted survival matrix (`distr`), results in 0 values, which are substituted by `"eps"` in our implementation, therefore skewing the result towards \eqn{-log(eps)}.
+#' This is the intractable likelihood problem discussed in Rindt et al. (2022), where the authors perform interpolation to get non-zero values for the \eqn{f(t)}.
+#' Until this is handled in `mlr3proba` some way, we advise against using this measure for model evaluation.
+#'
 #' @section Parameter details:
 #' - `na.rm` (`logical(1)`)\cr
 #' If `TRUE` (default) then removes any NAs in individual score calculations.
diff --git a/man/mlr_measures_surv.rcll.Rd b/man/mlr_measures_surv.rcll.Rd
index 405555ff9..bfec27951 100644
--- a/man/mlr_measures_surv.rcll.Rd
+++ b/man/mlr_measures_surv.rcll.Rd
@@ -13,6 +13,10 @@ The RCLL, in the context of probabilistic predictions, is defined by
 where \eqn{\Delta} is the censoring indicator, \eqn{f} the probability
 density function and \eqn{S} the survival function.
 RCLL is proper given that censoring and survival distribution are independent, see Rindt et al. (2022).
+
+\strong{Note}: Even though RCLL is a proper scoring rule, the calculation of \eqn{f(t)} (which in our case is discrete, i.e. it is a \emph{probability mass function}) for time points in the test set that don't exist in the predicted survival matrix (\code{distr}), results in 0 values, which are substituted by \code{"eps"} in our implementation, therefore skewing the result towards \eqn{-log(eps)}.
+This is the intractable likelihood problem discussed in Rindt et al. (2022), where the authors perform interpolation to get non-zero values for the \eqn{f(t)}.
+Until this is handled in \code{mlr3proba} some way, we advise against using this measure for model evaluation.
 }
 \section{Dictionary}{