diff --git a/.Rbuildignore b/.Rbuildignore
index b8486320..fc58474a 100644
--- a/.Rbuildignore
+++ b/.Rbuildignore
@@ -19,3 +19,4 @@
 ^CODE_OF_CONDUCT\.md$
 ^inst/manuscript/output$
 ^CRAN-SUBMISSION$
+^.vscode
diff --git a/NAMESPACE b/NAMESPACE
index f694e1e2..068c220a 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -82,7 +82,6 @@ export(quantile_score)
 export(score)
 export(se_mean_sample)
 export(select_metrics)
-export(set_forecast_unit)
 export(summarise_scores)
 export(summarize_scores)
 export(theme_scoringutils)
diff --git a/NEWS.md b/NEWS.md
index 2ca5f461..a8fff9c1 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -82,6 +82,7 @@ of our [original](https://doi.org/10.48550/arXiv.2205.07090) `scoringutils` pape
 - Removed the function `plot_score_table()`. You can find the code in the Deprecated-visualisations Vignette. 
 - Removed the function `merge_pred_and_obs()` that was used to merge two separate data frames with forecasts and observations. We moved its contents to a new "Deprecated functions"-vignette.
 - Removed `interval_coverage_sample()` as users are now expected to convert to a quantile format first before scoring.
+- Function `set_forecast_unit()` was deleted. Instead there is now a `forecast_unit` argument in `as_forecast_<type>()` as well as in `get_duplicate_forecasts()`.
 
 ### Function changes
 - `bias_quantile()` changed the way it handles forecasts where the median is missing: The median is now imputed by linear interpolation between the innermost quantiles. Previously, we imputed the median by simply taking the mean of the innermost quantiles.
diff --git a/R/convenience-functions.R b/R/convenience-functions.R
index 4bbb93da..3d8196f7 100644
--- a/R/convenience-functions.R
+++ b/R/convenience-functions.R
@@ -266,12 +266,11 @@ log_shift <- function(x, offset = 0, base = exp(1)) {
 #'   scoring or denote the unit of a single forecast as specified by the user.
 #' @importFrom data.table ':=' is.data.table copy
 #' @importFrom checkmate assert_character assert_subset
-#' @export
 #' @keywords as_forecast
 #' @examples
 #' library(magrittr) # pipe operator
 #' example_quantile %>%
-#'   set_forecast_unit(
+#'   scoringutils:::set_forecast_unit(
 #'     c("location", "target_end_date", "target_type", "horizon", "model")
 #'   )
 set_forecast_unit <- function(data, forecast_unit) {
diff --git a/R/forecast.R b/R/forecast.R
index ac17d1f4..4165d2d7 100644
--- a/R/forecast.R
+++ b/R/forecast.R
@@ -16,7 +16,7 @@
 #' existing columns of their input data to match the required columns for a
 #' forecast object. Using the argument `forecast_unit`, users can specify the
 #' the columns that uniquely identify a single forecast (and remove the others,
-#' see [set_forecast_unit()] for details).
+#' see docs for the internal [set_forecast_unit()] for details).
 #'
 #' The following functions are available:
 #' - [as_forecast_point()]
diff --git a/R/get_-functions.R b/R/get_-functions.R
index b0038cd4..3836f75a 100644
--- a/R/get_-functions.R
+++ b/R/get_-functions.R
@@ -279,11 +279,11 @@ get_protected_columns <- function(data = NULL) {
 #' @title Find duplicate forecasts
 #'
 #' @description
-#' Helper function to identify duplicate forecasts, i.e.
+#' Internal helper function to identify duplicate forecasts, i.e.
 #' instances where there is more than one forecast for the same prediction
 #' target.
 #'
-#' @param data A data.frame as used for [score()]
+#' @inheritParams as_forecast
 #' @param counts Should the output show the number of duplicates per forecast
 #'   unit instead of the individual duplicated rows? Default is `FALSE`.
 #' @return A data.frame with all rows for which a duplicate forecast was found
@@ -297,10 +297,15 @@ get_protected_columns <- function(data = NULL) {
 
 get_duplicate_forecasts <- function(
   data,
+  forecast_unit = NULL,
   counts = FALSE
 ) {
   assert_data_frame(data)
   data <- ensure_data.table(data)
+
+  if (!is.null(forecast_unit)) {
+    data <- set_forecast_unit(data, forecast_unit)
+  }
   forecast_unit <- get_forecast_unit(data)
   available_type <- c("sample_id", "quantile_level", "predicted_label") %in% colnames(data)
   type <- c("sample_id", "quantile_level", "predicted_label")[available_type]
diff --git a/man/as_forecast.Rd b/man/as_forecast.Rd
index 629ee10d..f57886dc 100644
--- a/man/as_forecast.Rd
+++ b/man/as_forecast.Rd
@@ -48,7 +48,7 @@ Using the arguments \code{observed}, \code{predicted}, \code{model}, etc. users
 existing columns of their input data to match the required columns for a
 forecast object. Using the argument \code{forecast_unit}, users can specify the
 the columns that uniquely identify a single forecast (and remove the others,
-see \code{\link[=set_forecast_unit]{set_forecast_unit()}} for details).
+see docs for the internal \code{\link[=set_forecast_unit]{set_forecast_unit()}} for details).
 
 The following functions are available:
 \itemize{
diff --git a/man/check_duplicates.Rd b/man/check_duplicates.Rd
index d39df769..7473f1e1 100644
--- a/man/check_duplicates.Rd
+++ b/man/check_duplicates.Rd
@@ -7,7 +7,9 @@
 check_duplicates(data)
 }
 \arguments{
-\item{data}{A data.frame as used for \code{\link[=score]{score()}}}
+\item{data}{A data.frame (or similar) with predicted and observed values.
+See the details section of \code{\link[=as_forecast]{as_forecast()}} for additional information
+on required input formats.}
 }
 \value{
 Returns TRUE if the check was successful and a string with an
diff --git a/man/get_duplicate_forecasts.Rd b/man/get_duplicate_forecasts.Rd
index db6f5a89..298d0bd5 100644
--- a/man/get_duplicate_forecasts.Rd
+++ b/man/get_duplicate_forecasts.Rd
@@ -4,10 +4,19 @@
 \alias{get_duplicate_forecasts}
 \title{Find duplicate forecasts}
 \usage{
-get_duplicate_forecasts(data, counts = FALSE)
+get_duplicate_forecasts(data, forecast_unit = NULL, counts = FALSE)
 }
 \arguments{
-\item{data}{A data.frame as used for \code{\link[=score]{score()}}}
+\item{data}{A data.frame (or similar) with predicted and observed values.
+See the details section of \code{\link[=as_forecast]{as_forecast()}} for additional information
+on required input formats.}
+
+\item{forecast_unit}{(optional) Name of the columns in \code{data} (after
+any renaming of columns) that denote the unit of a
+single forecast. See \code{\link[=get_forecast_unit]{get_forecast_unit()}} for details.
+If \code{NULL} (the default), all columns that are not required columns are
+assumed to form the unit of a single forecast. If specified, all columns
+that are not part of the forecast unit (or required columns) will be removed.}
 
 \item{counts}{Should the output show the number of duplicates per forecast
 unit instead of the individual duplicated rows? Default is \code{FALSE}.}
@@ -16,7 +25,7 @@ unit instead of the individual duplicated rows? Default is \code{FALSE}.}
 A data.frame with all rows for which a duplicate forecast was found
 }
 \description{
-Helper function to identify duplicate forecasts, i.e.
+Internal helper function to identify duplicate forecasts, i.e.
 instances where there is more than one forecast for the same prediction
 target.
 }
diff --git a/man/set_forecast_unit.Rd b/man/set_forecast_unit.Rd
index 53ca80d8..d609442e 100644
--- a/man/set_forecast_unit.Rd
+++ b/man/set_forecast_unit.Rd
@@ -36,7 +36,7 @@ easier to debug and easier to read.
 \examples{
 library(magrittr) # pipe operator
 example_quantile \%>\%
-  set_forecast_unit(
+  scoringutils:::set_forecast_unit(
     c("location", "target_end_date", "target_type", "horizon", "model")
   )
 }
diff --git a/tests/testthat/test-get_-functions.R b/tests/testthat/test-get_-functions.R
index 6a785778..4e765e29 100644
--- a/tests/testthat/test-get_-functions.R
+++ b/tests/testthat/test-get_-functions.R
@@ -165,6 +165,14 @@ test_that("get_type() handles `NA` values", {
 # get_duplicate_forecasts()
 # ==============================================================================
 test_that("get_duplicate_forecasts() works as expected for quantile", {
+  expect_no_condition(get_duplicate_forecasts(
+    example_quantile,
+    forecast_unit =
+      c("location", "target_end_date", "target_type", "location_name",
+        "forecast_date", "model")
+    )
+  )
+
   expect_equal(nrow(get_duplicate_forecasts(example_quantile)), 0)
   expect_equal(
     nrow(