diff --git a/R/apes.R b/R/apes.R
index ac0d52d..ef1b020 100644
--- a/R/apes.R
+++ b/R/apes.R
@@ -266,7 +266,7 @@ apes <- function(
 
 #' srr_stats
 #' @srrstats {G2.0} Implements assertions to ensure valid scaling relationships between population size and sample size.
-#' @srrstatsTODO {G2.0a} The main function explains that the inputs are unidimensional or the function gives an error.
+#' @srrstats {G2.0a} The main function explains that the inputs are unidimensional or the function gives an error.
 #' @srrstats {G5.2a} Issues clear warnings for invalid population adjustments or mismatched sizes.
 #' @noRd
 NULL
diff --git a/R/capybara-package.R b/R/capybara-package.R
index 2667dac..0511567 100644
--- a/R/capybara-package.R
+++ b/R/capybara-package.R
@@ -15,7 +15,13 @@
 #'  in this implementation compare to base R.
 #' @srrstats {G1.6} To keep dependencies minimal, we compare against base R in
 #'  the tests. An alternative would be to compare against alpaca.
-#' @srrstatsNA {G5.6a} No randomness in parameter estimation; deterministic methods used.
+#' @noRd
+NULL
+
+#' NA_standards
+#' @srrstatsNA {G5.6b} No randomness is needed for the in fixed effects
+#'  estimation. With the model slopes, recovering the fixed effects is a
+#'  deterministic process.
 #' @srrstatsNA {RE7.0a} No cross-validation implemented in this package.
 #' @noRd
 NULL
diff --git a/R/feglm_control.R b/R/feglm_control.R
index 762e665..3fd06df 100644
--- a/R/feglm_control.R
+++ b/R/feglm_control.R
@@ -1,7 +1,7 @@
 #' srr_stats
 #' @srrstats {G1.0} Implements controls for efficient and numerically stable fitting of generalized linear models with fixed effects.
 #' @srrstats {G2.0} Validates numeric input parameters to ensure they meet constraints (e.g., positive tolerance levels).
-#' @srrstatsTODO {G2.0a} The main function explains that the tolerance must be unidimensional or the function gives an error.
+#' @srrstats {G2.0a} The main function explains that the tolerance must be unidimensional or the function gives an error.
 #' @srrstats {G2.1a} Ensures the proper data types for arguments (e.g., logical for `trace`, integer for `iter_max`).
 #' @srrstats {G2.3a} Uses argument validation to ensure appropriate ranges for critical parameters (e.g., `iter_max` and `limit` >= 1).
 #' @srrstats {G2.14a} Provides informative error messages when tolerance levels or iteration counts are invalid.