diff --git a/DESCRIPTION b/DESCRIPTION
index a36d2a946..1cae564dd 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: portalcasting
 Title: Functions Used in Predicting Portal Rodent Dynamics
-Version: 0.35.0
+Version: 0.37.0
 Authors@R: c(
     person(c("Juniper", "L."), "Simonis",
       email = "juniper.simonis@weecology.org", role = c("aut", "cre"),
diff --git a/NEWS.md b/NEWS.md
index 8e0c74d8a..ee7124c86 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -2,6 +2,15 @@
 
 Version numbers follow [Semantic Versioning](https://semver.org/).
 
+# [portalcasting 0.37.0](https://github.com/weecology/portalcasting/releases/tag/v0.37.0)
+*2022-04-21*
+
+### Building out evaluation pipeline
+* starting with what is already occurring, but formalizing as such as part of an `evaluate_casts` and `evaluate_cast` pair of functions
+* `evaluate_casts` function now works automatically to evaluate all the casts using `evaluate_cast`, generating the error table as it does when being used, but nothing is saved out or updated.
+* there is also no filter on evaluated casts by deafult, so the output from the forecasts without observations to evaluate is a table with a single row with NaN, and then they get wrapped up into the list. 
+  * no errors, just noteworthy
+
 # [portalcasting 0.36.0](https://github.com/weecology/portalcasting/releases/tag/v0.36.0)
 *2022-04-08*
 
diff --git a/R/create_dir.R b/R/create_dir.R
index c85165047..1e7cc1824 100644
--- a/R/create_dir.R
+++ b/R/create_dir.R
@@ -8,6 +8,8 @@
 #'
 #' @param settings \code{list} of controls for the directory, with defaults set in \code{\link{directory_settings}}.
 #'
+#' @param verbose \code{logical} indicator of whether or not to print out all of the information (and thus just the tidy messages).
+#'
 #' @return The \code{list} of directory settings \code{\link[base]{invisible}}-ly.
 #'
 #' @name directory creation
@@ -31,10 +33,9 @@ create_dir <- function(main     = ".",
          showWarnings = FALSE)
 
 
-  config <- write_directory_config(main     = main, 
-                                   settings = settings, 
-                                   quiet    = quiet)
+  write_directory_config(main     = main, 
+                         settings = settings, 
+                         quiet    = quiet)
+
 
-  invisible(config)
- 
 }
diff --git a/R/directory_configuration_file.R b/R/directory_configuration_file.R
index efd303d06..32a650432 100644
--- a/R/directory_configuration_file.R
+++ b/R/directory_configuration_file.R
@@ -7,6 +7,8 @@
 #'
 #' @param quiet \code{logical} indicator if progress messages should be quieted.
 #'
+#' @param verbose \code{logical} indicator of whether or not to print out all of the information (and thus just the tidy messages).
+#'
 #' @param main \code{character} value of the name of the main component of the directory tree. Default value (\code{"."}) puts the forecasting directory in the present locations. Nesting the forecasting directory in a folder can be done by simply adding to the \code{main} input (see \code{Examples}).
 #'
 #' @param settings \code{list} of controls for the directory, with defaults set in \code{\link{directory_settings}} that should generally not need to be altered.
@@ -34,6 +36,7 @@ write_directory_config <- function (main     = ".",
 
   write_yaml(x    = config, 
              file = file.path(main, settings$files$directory_config))
+
   invisible(config)
 
 }
@@ -69,7 +72,8 @@ read_directory_config <- function (main     = ".",
 #'
 update_directory_config <- function (main     = ".", 
                                      settings = directory_settings(), 
-                                     quiet    = FALSE){
+                                     quiet    = FALSE,
+                                     verbose  = FALSE){
   
   config <- read_directory_config(main     = main, 
                                   settings = settings,
@@ -85,14 +89,13 @@ update_directory_config <- function (main     = ".",
 
     config$raw$PortalData_version <- scan(file  = file.path(main, settings$subs$resources, "PortalData", "version.txt"),
                                           what  = "character", 
-                                          quiet = TRUE)
+                                          quiet = !verbose)
 
   }
 
-
-
   write_yaml(x    = config, 
              file = file.path(main, settings$files$directory_config))
+
   invisible(config)
 
 }
diff --git a/R/evaluate.R b/R/evaluate.R
index 8f4fc4912..77365d6ae 100644
--- a/R/evaluate.R
+++ b/R/evaluate.R
@@ -1,5 +1,3 @@
-
-
 #' @title Evaluate Forecasts
 #'
 #' @description Evaluate forecasts in the directory, based on id or group, or (if \code{cast_ids = NULL} and \code{cast_groups = NULL}, the default) \code{evaluate_casts} will evaluate all and (if \code{cast_id = NULL} and \code{cast_group = NULL}, the default), \code{evaluate_cast} will evaluate the most recent cast.
@@ -8,9 +6,6 @@
 #'
 #' @param settings \code{list} of controls for the directory, with defaults set in \code{\link{directory_settings}} that should generally not need to be altered.
 #'
-#' @param cast_group,cast_groups \code{integer} (or integer \code{numeric}) value(s) of the cast group(s) to evaluate, as indexed within the directory in the \code{casts} sub folder. See the casts metadata file (\code{casts_metadata.csv}) for summary information. \cr
-#'  \code{cast_group} can only be a single value, whereas \code{cast_groups} can be multiple.
-#'
 #' @param cast_id,cast_ids \code{integer} (or integer \code{numeric}) value(s) representing the casts of interest for evaluating, as indexed within the directory in the \code{casts} sub folder. See the casts metadata file (\code{casts_metadata.csv}) for summary information. \cr
 #'  \code{cast_id} can only be a single value, whereas \code{cast_ids} can be multiple.
 #'
@@ -18,22 +13,47 @@
 #'
 #' @param verbose \code{logical} indicator of whether or not to print out all of the information (and thus just the tidy messages).
 #'
-#' @return \code{NULL}, \code{\link[base]{invisible}}-ly.
+#' @return A \code{data.frame}, or \code{list} of \code{data.frame}s.
 #'
 #' @name evaluate forecasts
 #'
 #' @export
 #'
-evaluate_casts <- function (main        = ".", 
-                            settings    = directory_settings(), 
-                            cast_groups = NULL, 
-                            cast_ids    = NULL,
-                            quiet       = FALSE, 
-                            verbose     = FALSE) {
+evaluate_casts <- function (main     = ".", 
+                            settings = directory_settings(), 
+                            cast_ids = NULL,
+                            quiet    = FALSE, 
+                            verbose  = FALSE) {
+
+
+  casts_to_evaluate <- select_casts(main     = main, 
+                                    settings = settings,
+                                    cast_ids = cast_ids)
+
+  if (NROW(casts_to_evaluate) == 0) {
+
+    stop("no casts available for request")
 
+  } else {
 
+    cast_ids  <- casts_to_evaluate$cast_id
+    ncast_ids <- length(cast_ids)
 
-  invisible()
+  }
+
+  out <- named_null_list(element_names = cast_ids)
+
+  for (i in 1:ncast_ids) {
+
+    out[[i]] <- evaluate_cast(main     = main,
+                              settings = settings,
+                              cast_id  = cast_ids[i],
+                              quiet    = quiet,
+                              verbose  = verbose)
+
+  }
+
+  out
 
 }
 
@@ -42,16 +62,43 @@ evaluate_casts <- function (main        = ".",
 #'
 #' @export
 #'
-evaluate_cast <- function (main       = ".", 
-                           settings   = directory_settings(), 
-                           cast_group = NULL, 
-                           cast_id    = NULL,
-                           quiet      = FALSE, 
-                           verbose    = FALSE) {
+evaluate_cast <- function (main     = ".", 
+                           settings = directory_settings(), 
+                           cast_id  = NULL,
+                           quiet    = FALSE, 
+                           verbose  = FALSE) {
+
+  return_if_null(cast_id)
+
+  model_cast     <- read_model_cast(main     = main,
+                                    cast_id  = cast_id,
+                                    settings = settings)
+  casts_metadata <- read_casts_metadata(main     = main,
+                                       settings = settings)
+  cast_model     <- casts_metadata$model[casts_metadata$cast_id == cast_id]
 
+  cast_model_controls <- model_controls(main     = main,
+                                        models   = cast_model,
+                                        settings = settings)[[cast_model]]
+  cast_model_response <- cast_model_controls$response
 
+  cast_tab <- read_cast_tab(main     = main, 
+                            settings = settings,
+                            cast_id  = cast_id)
 
-  invisible()
+  cast_tab <- add_obs_to_cast_tab(main     = main,  
+                                  settings = settings,
+                                  cast_tab = cast_tab)
+  cast_tab <- add_err_to_cast_tab(main     = main,  
+                                  settings = settings,
+                                  cast_tab = cast_tab)
+  cast_tab <- add_lead_to_cast_tab(main     = main,  
+                                   settings = settings,
+                                   cast_tab = cast_tab)
+  cast_tab <- add_covered_to_cast_tab(main     = main,  
+                                      settings = settings,
+                                      cast_tab = cast_tab)
+  measure_cast_level_error(cast_tab = cast_tab)
 
 }
 
diff --git a/R/portalcast.R b/R/portalcast.R
index c48dc00fd..cc5fdfba6 100644
--- a/R/portalcast.R
+++ b/R/portalcast.R
@@ -46,6 +46,11 @@ portalcast <- function (main       = ".",
                         quiet      = FALSE,
                         verbose    = FALSE){
 
+#
+# the datasets here should come from the models selected
+#  and not as an argument ... or? maybe not? idk. think this out.
+# 
+
   return_if_null(models)
 
   messageq(message_break(), "\nPreparing directory for casting\n", message_break(), "\nThis is portalcasting v", packageDescription("portalcasting", fields = "Version"), "\n", message_break(), quiet = quiet)
diff --git a/R/prepare_models.R b/R/prepare_models.R
index d6e3223f3..e18cd6b44 100644
--- a/R/prepare_models.R
+++ b/R/prepare_models.R
@@ -1,6 +1,6 @@
 #' @title Read and Write Model Control Lists
 #'
-#' @description Input/Output functions for model control lists.
+#' @description Input/output functions for model control lists.
 #'
 #' @param quiet \code{logical} indicator controlling if messages are printed.
 #'
@@ -75,6 +75,10 @@ write_model_controls <- function (main               = ".",
 }
 
 
+
+
+
+
 #' @title Write Model Function Script into Directory
 #'
 #' @description Writes a model's function as a script into the defined directory for use in forecasting. \cr \cr \code{model} can be input as a \code{character} string, symbol (backquoted name), or \code{function}, as \code{\link{match.fun}}
diff --git a/R/process_casts.R b/R/process_casts.R
index b63b39772..3bc9aabe9 100644
--- a/R/process_casts.R
+++ b/R/process_casts.R
@@ -221,8 +221,8 @@ add_obs_to_cast_tab <- function (main     = ".",
 #' @export
 #'
 read_cast_tab <- function (main     = ".", 
-                           settings = directory_settings(), 
-                           cast_id  = NULL) {
+                           cast_id  = NULL, 
+                           settings = directory_settings()) {
 
   if (is.null(cast_id) ){
 
@@ -257,8 +257,8 @@ read_cast_tab <- function (main     = ".",
 #' @export
 #'
 read_cast_tabs <- function (main     = ".", 
-                            settings = directory_settings(), 
-                            cast_ids  = NULL) {
+                            cast_ids  = NULL, 
+                            settings = directory_settings()) {
   
   if (is.null(cast_ids)) {
 
@@ -269,8 +269,8 @@ read_cast_tabs <- function (main     = ".",
   }
 
   cast_tab <- read_cast_tab(main     = main,
-                            settings = settings,
-                            cast_id  = cast_ids[1])
+                            cast_id  = cast_ids[1],
+                            settings = settings)
   ncasts   <- length(cast_ids)
 
 
@@ -278,9 +278,9 @@ read_cast_tabs <- function (main     = ".",
 
     for (i in 2:ncasts) {
 
-      cast_tab_i <- read_cast_tab(main     = main, 
-                                  settings = settings,
-                                  cast_id  = cast_ids[i])
+      cast_tab_i <- read_cast_tab(main     = main,
+                                  cast_id  = cast_ids[i], 
+                                  settings = settings)
 
       cast_tab   <- rbind(cast_tab, cast_tab_i)
 
@@ -297,8 +297,8 @@ read_cast_tabs <- function (main     = ".",
 #' @export
 #'
 read_cast_metadata <- function (main     = ".", 
-                                settings = directory_settings(), 
-                                cast_id  = NULL) {
+                                cast_id  = NULL, 
+                                settings = directory_settings()) {
   
   if (is.null(cast_id)) {
 
@@ -326,8 +326,8 @@ read_cast_metadata <- function (main     = ".",
 #' @export
 #'
 read_model_fit <- function (main     = ".", 
-                            settings = directory_settings(), 
-                            cast_id  = NULL) {
+                            cast_id  = NULL, 
+                            settings = directory_settings()) {
   
   if (is.null(cast_id)) {
 
@@ -356,8 +356,8 @@ read_model_fit <- function (main     = ".",
 #' @export
 #'
 read_model_cast <- function (main     = ".", 
-                             settings = directory_settings(), 
-                             cast_id  = NULL) {
+                             cast_id  = NULL, 
+                             settings = directory_settings()) {
   
   if (is.null(cast_id)) {
 
@@ -367,17 +367,32 @@ read_model_cast <- function (main     = ".",
 
   }
 
-  lpath <- paste0("cast_id_", cast_id, "_model_casts.json")
-  cpath <- file.path(main, settings$subs$forecasts, lpath)
+  lpath_json  <- paste0("cast_id_", cast_id, "_model_casts.json")
+  cpath_json  <- file.path(main, settings$subs$forecasts, lpath_json)
 
-  if (!file.exists(cpath)) {
+  lpath_RData <- paste0("cast_id_", cast_id, "_model_casts.RData")
+  cpath_RData  <- file.path(main, settings$subs$forecasts, lpath_RData)
 
-    stop("cast_id does not have a model_casts file")
+  if (!file.exists(cpath_json)) {
 
-  }
+    if (!file.exists(cpath_RData)) {
 
-  read_in_json <- fromJSON(readLines(cpath))
-  unserializeJSON(read_in_json)
+      stop("cast_id does not have a model_casts file")
+  
+    } else {
+
+      model_casts <- NULL
+      load(cpath_RData)
+      model_casts
+
+    }
+
+  } else {
+
+    read_in_json <- fromJSON(readLines(cpath_json))
+    unserializeJSON(read_in_json)
+
+  }
 
 }
 
@@ -483,12 +498,12 @@ select_casts <- function (main           = ".",
 #'    of the model (across multiple species, for example). 
 #'   \item \code{"model_fits"}: saved out as a serialized \code{JSON} file 
 #'    via \code{\link[jsonlite]{serializeJSON}} and 
-#'    \code{\link[jsonlite]{write_json}}, so quite flexible with respect to 
+#'    \code{\link[jsonlite:read_json]{write_json}}, so quite flexible with respect to 
 #'    specific object structure. Saving out a \code{list} of the actual model
 #'    fit/return objects means that models do not need to be refit later.
 #'   \item \code{"model_casts"}: saved out as a serialized \code{JSON} file 
 #'    via \code{\link[jsonlite]{serializeJSON}} and 
-#'    \code{\link[jsonlite]{write_json}}, so quite flexible with respect to 
+#'    \code{\link[jsonlite:read_json]{write_json}}, so quite flexible with respect to 
 #'    specific object structure. Is used to save \code{list}s
 #'    of predictions across multiple instances of the model.
 #'  }
diff --git a/R/rodent_species.R b/R/rodent_species.R
index 1471a9029..acaec8e0e 100644
--- a/R/rodent_species.R
+++ b/R/rodent_species.R
@@ -109,10 +109,9 @@ rodent_species <- function (set   = NULL,
 
     stop ("`type` must be `NULL`, 'all', 'base', or 'eval'")    
  
-
   }
 
-  if (nadot) {
+  if (total) {
 
     out_abb[which(out_abb == "NA")] <- "NA."
 
diff --git a/code_development/hold_modelcontrols.R b/code_development/hold_modelcontrols.R
deleted file mode 100644
index 53c586399..000000000
--- a/code_development/hold_modelcontrols.R
+++ /dev/null
@@ -1,52 +0,0 @@
-
-  list(
-    AutoArima     = list(metadata        = list(name            = "AutoArima",  
-                                                descriptor      = "classic model, all species, focal species"),
-                         fun             = "AutoArima",
-                         args            = NULL,
-                         datasets        = c("all", "controls", "exclosures", "dm_controls")), 
-    ESSS          = list(metadata        = list(name            = "ESSS",  
-                                                descriptor      = "classic model, all species, focal species"),
-                         fun             = "ESSS",
-                         args            = NULL,
-                         datasets        = c("all_interp", "controls_interp", "exclosures_interp", "dm_controls_interp")),
-    NaiveArima    = list(metadata        = list(name            = "NaiveArima",  
-                                                descriptor      = "classic model, all species, focal species"),
-                         fun             = "NaiveArima",
-                         args            = NULL,
-                         datasets        = c("all", "controls", "exclosures", "dm_controls")), 
-    nbGARCH       = list(metadata        = list(name            = "nbGARCH",  
-                                                descriptor      = "classic model, all species, focal species"),
-                         fun             = "nbGARCH",
-                         args            = NULL,
-                         datasets        = c("all_interp", "controls_interp", "exclosures_interp", "dm_controls_interp")), 
-    nbsGARCH      = list(metadata        = list(name            = "nbsGARCH",  
-                                                descriptor      = "classic model, all species, focal species"),
-                         fun             = "nbsGARCH",
-                         args            = NULL,
-                         datasets        = c("all_interp", "controls_interp", "exclosures_interp", "dm_controls_interp")), 
-    pevGARCH      = list(metadata        = list(name            = "pevGARCH", 
-                                                descriptor      = "classic model, all species, focal species"),  
-                         fun             = "pevGARCH",
-                         datasets        = c("all_interp", "controls_interp", "exclosures_interp", "dm_controls_interp"),
-                         args            = list(lag = 6)), 
-#    simplexEDM    = list(metadata        = list(name            = "simplexEDM",  
-#                                                descriptor      = "population model, all species, focal species"),
-#                         fun             = "simplexEDM",
-#                         datasets        = c("all_interp", "controls_interp", "exclosures_interp", "dm_controls_interp"), 
-#                         args            = list(max_E           = 7)),
-#    GPEDM         = list(metadata        = list(name            = "GPEDM",  
-#                                                descriptor      = "population model, all species, focal species"),
-#                         fun             = "GPEDM",
-#                         datasets        = c("all_interp", "controls_interp", "exclosures_interp", "dm_controls_interp"), 
-#                         args            = list(max_E           = 7)),
-    jags_RW       = list(metadata        = list(name            = "jags_RW",  
-                                                descriptor      = "population model, focal species"),
-                         fun             = "jags_RW",
-                         datasets        = c("dm_controls"), 
-                         args            = list(control_runjags = runjags_control())),
-    jags_logistic = list(metadata =        list(name            = "jags_logistic", 
-                                                descriptor      = "population model, focal species"),
-                         fun             = "jags_logistic",
-                         datasets        = c("dm_controls"), 
-                         args            = list(control_runjags = runjags_control())))
diff --git a/code_development/hold_rodentcontrols.R b/code_development/hold_rodentcontrols.R
deleted file mode 100644
index dc3a33771..000000000
--- a/code_development/hold_rodentcontrols.R
+++ /dev/null
@@ -1,200 +0,0 @@
-prefab_rodent_dataset_controls <- function(interpolate = NULL) {
-  out <- list(
-    all                = list(metadata = list(name       = "all", 
-                                              descriptor = "classic dataset, all plots combined"),
-                              fun      = "prep_rodent_dataset",
-                              args     = list(name        = "all", 
-                                              species     = base_species(), 
-                                              total       = TRUE,
-                                              interpolate = FALSE, 
-                                              clean       = FALSE, 
-                                              type        = "Rodents", 
-                                              level       = "Site", 
-                                              plots       = "all", 
-                                              treatment   = NULL, 
-                                              min_plots   = 24, 
-                                              min_traps   = 1, 
-                                              output      = "abundance", 
-                                              fillweight  = FALSE, 
-                                              unknowns    = FALSE, 
-                                              time        = "newmoon", 
-                                              na_drop     = FALSE, 
-                                              zero_drop   = TRUE, 
-                                              effort      = TRUE,
-                                              filename    = "rodents_all.csv")),
-    all_interp         = list(metadata = list(name = "all_interp", 
-                                              descriptor = "classic dataset, all plots combined, interpolated for models that cannot have missing data"),
-                              fun      = "prep_rodent_dataset",
-                              args     = list(name        = "all_interp", 
-                                              species     = base_species(), 
-                                              total       = TRUE,
-                                              interpolate = TRUE, 
-                                              clean       = FALSE, 
-                                              type        = "Rodents", 
-                                              level       = "Site", 
-                                              plots       = "all", 
-                                              treatment   = NULL, 
-                                              min_plots   = 24, 
-                                              min_traps   = 1,
-                                              output      = "abundance", 
-                                              fillweight  = FALSE, 
-                                              unknowns    = FALSE, 
-                                              time        = "newmoon", 
-                                              na_drop     = FALSE, 
-                                              zero_drop   = TRUE, 
-                                              effort      = TRUE, 
-                                              filename    = "rodents_all_interp.csv")),
-    controls           = list(metadata = list(name = "controls", 
-                                              descriptor = "classic dataset, control plots combined"),
-                              fun      = "prep_rodent_dataset",
-                              args     = list(name        = "controls", 
-                                              species     = base_species(), 
-                                              total       = TRUE, 
-                                              interpolate = FALSE, 
-                                              clean       = FALSE, 
-                                              type        = "Rodents", 
-                                              level       = "Treatment", 
-                                              plots       = "Longterm", 
-                                              treatment   = "control", 
-                                              min_plots   = 24, 
-                                              min_traps   = 1, 
-                                              output      = "abundance", 
-                                              fillweight  = FALSE, 
-                                              unknowns    = FALSE, 
-                                              time        = "newmoon", 
-                                              na_drop     = FALSE, 
-                                              zero_drop   = TRUE, 
-                                              effort      = TRUE, 
-                                              filename    = "rodents_controls.csv")),
-    controls_interp    = list(metadata = list(name = "controls_interp", 
-                                              descriptor = "classic dataset, control plots combined, interpolated for models that cannot have missing data"),
-                              fun      = "prep_rodent_dataset",
-                              args     = list(name        = "controls_interp", 
-                                              species     = base_species(), 
-                                              total       = TRUE, 
-                                              interpolate = TRUE, 
-                                              clean       = FALSE, 
-                                              type        = "Rodents", 
-                                              level       = "Treatment", 
-                                              plots       = "Longterm", 
-                                              treatment   = "control", 
-                                              min_plots   = 24, 
-                                              min_traps   = 1, 
-                                              output      = "abundance", 
-                                              fillweight  = FALSE, 
-                                              unknowns    = FALSE, 
-                                              time        = "newmoon", 
-                                              na_drop     = FALSE, 
-                                              zero_drop   = TRUE, 
-                                              effort      = TRUE, 
-                                              filename    = "rodents_controls_interp.csv")),
-    exclosures         = list(metadata = list(name = "exclosures", 
-                                              descriptor = "classic dataset, exclosure plots combined"),
-                              fun      = "prep_rodent_dataset",
-                              args     = list(name        = "exclosures", 
-                                              species     = base_species(), 
-                                              total       = TRUE,  
-                                              interpolate = FALSE, 
-                                              clean       = FALSE, 
-                                              type        = "Rodents",  
-                                              level       = "Treatment", 
-                                              plots       = "Longterm",  
-                                              treatment   = "exclosure", 
-                                              min_plots   = 24,  
-                                              min_traps   = 1, 
-                                              output      = "abundance",  
-                                              fillweight  = FALSE, 
-                                              unknowns    = FALSE,  
-                                              time        = "newmoon", 
-                                              na_drop     = FALSE, 
-                                              zero_drop   = TRUE, 
-                                              effort      = TRUE, 
-                                              filename    = "rodents_exclosures.csv")),
-    exclosures_interp  = list(metadata = list(name = "exclosures_interp", 
-                                              descriptor = "classic dataset, exclosure plots combined, interpolated for models that cannot have missing data"),
-                              fun      = "prep_rodent_dataset",
-                              args     = list(name        = "exclosures_interp", 
-                                              species     = base_species(), 
-                                              total       = TRUE,  
-                                              interpolate = TRUE, 
-                                              clean       = FALSE, 
-                                              type        = "Rodents",  
-                                              level       = "Treatment", 
-                                              plots       = "Longterm",  
-                                              treatment   = "exclosure", 
-                                              min_plots   = 24,  
-                                              min_traps   = 1, 
-                                              output      = "abundance",  
-                                              fillweight  = FALSE, 
-                                              unknowns    = FALSE,  
-                                              time        = "newmoon", 
-                                              na_drop     = FALSE, 
-                                              zero_drop   = TRUE, 
-                                              effort      = TRUE, 
-                                              filename    = "rodents_exclosures_interp.csv")),
-    dm_controls        = list(metadata = list(name = "dm_controls", 
-                                              descriptor = "DM only, control plots combined"),
-                              fun      = "prep_rodent_dataset",
-                              args     = list(name        = "dm_controls",  
-                                              species     = "DM", 
-                                              total       = FALSE,  
-                                              interpolate = FALSE, 
-                                              clean       = FALSE, 
-                                              type        = "Rodents",  
-                                              level       = "Treatment", 
-                                              plots       = "Longterm",  
-                                              treatment   = "control", 
-                                              min_plots   = 24,  
-                                              min_traps   = 1, 
-                                              output      = "abundance",  
-                                              fillweight  = FALSE, 
-                                              unknowns    = FALSE,  
-                                              time        = "newmoon", 
-                                              na_drop     = FALSE, 
-                                              zero_drop   = TRUE, 
-                                              effort      = TRUE, 
-                                              filename    = "rodents_dm_controls.csv")),
-    dm_controls_interp = list(metadata = list(name = "dm_controls_interp",  
-                                              descriptor = "DM only, control plots combined, interpolated for models that cannot have missing data"),
-                              fun      = "prep_rodent_dataset",
-                              args     = list(name        = "dm_controls_interp",  
-                                              species     = "DM", 
-                                              total       = FALSE,  
-                                              interpolate = TRUE, 
-                                              clean       = FALSE, 
-                                              type        = "Rodents",  
-                                              level       = "Treatment", 
-                                              plots       = "Longterm",  
-                                              treatment   = "control", 
-                                              min_plots   = 24,  
-                                              min_traps   = 1, 
-                                              output      = "abundance",  
-                                              fillweight  = FALSE, 
-                                              unknowns    = FALSE,  
-                                              time        = "newmoon", 
-                                              na_drop     = FALSE, 
-                                              zero_drop   = TRUE, 
-                                              effort      = TRUE, 
-                                              filename    = "rodents_dm_controls_interp.csv")))
-
-  if (is.null(interpolate)) {
-
-    out
-
-  } else {
-
-    dsnames <- names(out)
-
-    if (interpolate) {
-
-      out[grepl("_interp", dsnames)]
-
-    } else {
-
-      out[!grepl("_interp", dsnames)]
-
-    }
-
-  }
-
-}
\ No newline at end of file
diff --git a/code_development/notes.R b/code_development/notes.R
index f3270abc1..cfa073c5b 100644
--- a/code_development/notes.R
+++ b/code_development/notes.R
@@ -4,7 +4,26 @@
 devtools::document()
 devtools::load_all()
 
-main <- "./portalcasting"
+main <- "~/portalcasting"
+
+
+setup_production(main = main)
+
+#
+# to do
+#
+#   in portalcast and cast
+#      datasets should come from the models' via their controls
+#
+
+
+
+
+
+
+
+
+
 
 
 
diff --git a/man/directory-creation.Rd b/man/directory-creation.Rd
index ca40aa0e1..1e0af117e 100644
--- a/man/directory-creation.Rd
+++ b/man/directory-creation.Rd
@@ -13,6 +13,8 @@ create_dir(main = ".", settings = directory_settings(), quiet = FALSE)
 \item{settings}{\code{list} of controls for the directory, with defaults set in \code{\link{directory_settings}}.}
 
 \item{quiet}{\code{logical} indicator if progress messages should be quieted.}
+
+\item{verbose}{\code{logical} indicator of whether or not to print out all of the information (and thus just the tidy messages).}
 }
 \value{
 The \code{list} of directory settings \code{\link[base]{invisible}}-ly.
diff --git a/man/directory_configuration_file.Rd b/man/directory_configuration_file.Rd
index 439e16020..776b30b18 100644
--- a/man/directory_configuration_file.Rd
+++ b/man/directory_configuration_file.Rd
@@ -22,7 +22,8 @@ read_directory_config(
 update_directory_config(
   main = ".",
   settings = directory_settings(),
-  quiet = FALSE
+  quiet = FALSE,
+  verbose = FALSE
 )
 }
 \arguments{
@@ -31,6 +32,8 @@ update_directory_config(
 \item{settings}{\code{list} of controls for the directory, with defaults set in \code{\link{directory_settings}} that should generally not need to be altered.}
 
 \item{quiet}{\code{logical} indicator if progress messages should be quieted.}
+
+\item{verbose}{\code{logical} indicator of whether or not to print out all of the information (and thus just the tidy messages).}
 }
 \value{
 \code{list} of directory configurations, \code{\link[base]{invisible}}-ly.
diff --git a/man/evaluate-forecasts.Rd b/man/evaluate-forecasts.Rd
index 9936cadbc..cdbddda80 100644
--- a/man/evaluate-forecasts.Rd
+++ b/man/evaluate-forecasts.Rd
@@ -9,7 +9,6 @@
 evaluate_casts(
   main = ".",
   settings = directory_settings(),
-  cast_groups = NULL,
   cast_ids = NULL,
   quiet = FALSE,
   verbose = FALSE
@@ -18,7 +17,6 @@ evaluate_casts(
 evaluate_cast(
   main = ".",
   settings = directory_settings(),
-  cast_group = NULL,
   cast_id = NULL,
   quiet = FALSE,
   verbose = FALSE
@@ -33,14 +31,11 @@ evaluate_cast(
 
 \item{verbose}{\code{logical} indicator of whether or not to print out all of the information (and thus just the tidy messages).}
 
-\item{cast_group, cast_groups}{\code{integer} (or integer \code{numeric}) value(s) of the cast group(s) to evaluate, as indexed within the directory in the \code{casts} sub folder. See the casts metadata file (\code{casts_metadata.csv}) for summary information. \cr
-\code{cast_group} can only be a single value, whereas \code{cast_groups} can be multiple.}
-
 \item{cast_id, cast_ids}{\code{integer} (or integer \code{numeric}) value(s) representing the casts of interest for evaluating, as indexed within the directory in the \code{casts} sub folder. See the casts metadata file (\code{casts_metadata.csv}) for summary information. \cr
 \code{cast_id} can only be a single value, whereas \code{cast_ids} can be multiple.}
 }
 \value{
-\code{NULL}, \code{\link[base]{invisible}}-ly.
+A \code{data.frame}, or \code{list} of \code{data.frame}s.
 }
 \description{
 Evaluate forecasts in the directory, based on id or group, or (if \code{cast_ids = NULL} and \code{cast_groups = NULL}, the default) \code{evaluate_casts} will evaluate all and (if \code{cast_id = NULL} and \code{cast_group = NULL}, the default), \code{evaluate_cast} will evaluate the most recent cast.
diff --git a/man/read-and-write-model-controls.Rd b/man/read-and-write-model-controls.Rd
index b53166edb..428fe7d5e 100644
--- a/man/read-and-write-model-controls.Rd
+++ b/man/read-and-write-model-controls.Rd
@@ -38,5 +38,5 @@ write_model_controls(
 \code{list} of \code{models}' control \code{list}s, \code{\link[base]{invisible}}-ly for \code{write_model_controls}.
 }
 \description{
-Input/Output functions for model control lists.
+Input/output functions for model control lists.
 }
diff --git a/man/read-cast-output.Rd b/man/read-cast-output.Rd
index 3eb0ce562..a61ccbe4e 100644
--- a/man/read-cast-output.Rd
+++ b/man/read-cast-output.Rd
@@ -9,15 +9,15 @@
 \alias{read_model_cast}
 \title{Read in Cast Output From a Given Cast}
 \usage{
-read_cast_tab(main = ".", settings = directory_settings(), cast_id = NULL)
+read_cast_tab(main = ".", cast_id = NULL, settings = directory_settings())
 
-read_cast_tabs(main = ".", settings = directory_settings(), cast_ids = NULL)
+read_cast_tabs(main = ".", cast_ids = NULL, settings = directory_settings())
 
-read_cast_metadata(main = ".", settings = directory_settings(), cast_id = NULL)
+read_cast_metadata(main = ".", cast_id = NULL, settings = directory_settings())
 
-read_model_fit(main = ".", settings = directory_settings(), cast_id = NULL)
+read_model_fit(main = ".", cast_id = NULL, settings = directory_settings())
 
-read_model_cast(main = ".", settings = directory_settings(), cast_id = NULL)
+read_model_cast(main = ".", cast_id = NULL, settings = directory_settings())
 }
 \arguments{
 \item{main}{\code{character} value of the name of the main component of the directory tree.}
diff --git a/man/save_cast_output.Rd b/man/save_cast_output.Rd
index ed1b898f5..9f618685d 100644
--- a/man/save_cast_output.Rd
+++ b/man/save_cast_output.Rd
@@ -41,12 +41,12 @@ Currently, four generalized output components are recognized and indicated by th
    of the model (across multiple species, for example). 
   \item \code{"model_fits"}: saved out as a serialized \code{JSON} file 
    via \code{\link[jsonlite]{serializeJSON}} and 
-   \code{\link[jsonlite]{write_json}}, so quite flexible with respect to 
+   \code{\link[jsonlite:read_json]{write_json}}, so quite flexible with respect to 
    specific object structure. Saving out a \code{list} of the actual model
    fit/return objects means that models do not need to be refit later.
   \item \code{"model_casts"}: saved out as a serialized \code{JSON} file 
    via \code{\link[jsonlite]{serializeJSON}} and 
-   \code{\link[jsonlite]{write_json}}, so quite flexible with respect to 
+   \code{\link[jsonlite:read_json]{write_json}}, so quite flexible with respect to 
    specific object structure. Is used to save \code{list}s
    of predictions across multiple instances of the model.
  }
diff --git a/tests/testthat/test-22-evaluate.R b/tests/testthat/test-22-evaluate.R
index 96b4f0be1..32ecc09d4 100644
--- a/tests/testthat/test-22-evaluate.R
+++ b/tests/testthat/test-22-evaluate.R
@@ -1,15 +1,18 @@
 context(desc = "evaluate functions")
 
+main <- "./testing"
+
 test_that(desc = "evaluate_casts evaluates casts", {
 
-  expect_null(evaluate_casts())
+  expect_is(evaluate_casts(main = main, cast_ids = 1:2), "list")
 
 })
 
 
 test_that(desc = "evaluate_cast evaluates cast", {
 
-  expect_null(evaluate_cast())
+  expect_null(evaluate_cast(main = main))
+  expect_is(evaluate_cast(main = main, cast_id = 1), "data.frame")
 
 })