diff --git a/DESCRIPTION b/DESCRIPTION
index a5a662a6..6186479b 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -25,7 +25,7 @@ Authors@R: c(
            family = "Burk",
            role = "rev")
     )
-Description: Fit, interpret, and make predictions with oblique random survival forests. Oblique decision trees are notoriously slow compared to their axis based counterparts, but 'aorsf' runs as fast or faster than axis-based decision tree algorithms for right-censored time-to-event outcomes. Methods to accelerate and interpret the oblique random survival forest are described in Jaeger et al., (2023) <DOI: 10.1080/10618600.2023.2231048>.
+Description: Fit, interpret, and make predictions with oblique random survival forests. Oblique decision trees are notoriously slow compared to their axis based counterparts, but 'aorsf' runs as fast or faster than axis-based decision tree algorithms for right-censored time-to-event outcomes. Methods to accelerate and interpret the oblique random survival forest are described in Jaeger et al., (2023) <DOI:10.1080/10618600.2023.2231048>.
 License: MIT + file LICENSE
 Encoding: UTF-8
 LazyData: true
diff --git a/R/roxy.R b/R/roxy.R
index afaa26e2..40844894 100644
--- a/R/roxy.R
+++ b/R/roxy.R
@@ -199,8 +199,8 @@ roxy_cite_jaeger_2023 <- function(){
   journal = "Journal of Computational and Graphical Statistics",
   date = "Published online 08 Aug 2023",
   number = NULL,
-  # doi = "10.1080/10618600.2023.2231048",
-  url = "https://doi.org/10.1080/10618600.2023.2231048"
+  doi = "10.1080/10618600.2023.2231048"
+  # url = "https://doi.org/10.1080/10618600.2023.2231048"
  )
 
 }
diff --git a/inst/CITATION b/inst/CITATION
index dbdb9abc..ca5f2143 100644
--- a/inst/CITATION
+++ b/inst/CITATION
@@ -2,13 +2,13 @@ citHeader("To cite aorsf in publications use:")
 
 
 
-citEntry(
-  entry    = "Article",
+bibentry(
+  bibtype  = "Article",
   title    = "aorsf: An R package for supervised learning using the oblique random survival forest",
-  author   = personList(as.person("Byron C. Jaeger"),
-                        as.person("Sawyer Welden"),
-                        as.person("Kristin Lenoir"),
-                        as.person("Nicholas M. Pajewski")),
+  author   = c(as.person("Byron C. Jaeger"),
+               as.person("Sawyer Welden"),
+               as.person("Kristin Lenoir"),
+               as.person("Nicholas M. Pajewski")),
   journal  = "Journal of Open Source Software",
   year     = "2022",
   volume   = "7",
@@ -22,16 +22,16 @@ citEntry(
   )
 )
 
-citEntry(
-  entry    = "Article",
+bibentry(
+  bibtype  =  "Article",
   title    = "Accelerated and interpretable oblique random survival forests",
-  author   = personList(as.person("Byron C. Jaeger"),
-                        as.person("Sawyer Welden"),
-                        as.person("Kristin Lenoir"),
-                        as.person("Jaime L. Speiser"),
-                        as.person("Matthew W. Segar"),
-                        as.person("Ambarish Pandey"),
-                        as.person("Nicholas M. Pajewski")),
+  author   = c(as.person("Byron C. Jaeger"),
+               as.person("Sawyer Welden"),
+               as.person("Kristin Lenoir"),
+               as.person("Jaime L. Speiser"),
+               as.person("Matthew W. Segar"),
+               as.person("Ambarish Pandey"),
+               as.person("Nicholas M. Pajewski")),
   journal  = "Journal of Computational and Graphical Statistics",
   year     = "2023",
   url      = "https://doi.org/10.1080/10618600.2023.2231048",
@@ -42,9 +42,10 @@ citEntry(
   )
 )
 
-citEntry(entry = "Article",
+bibentry(
+  bibtype      = "Article",
   title        = "Oblique Random Survival Forests",
-  author       = personList(
+  author       = c(
                    as.person("Byron C. Jaeger"),
                    as.person("D. Leann Long"),
                    as.person("Dustin M. Long"),
diff --git a/man/aorsf-package.Rd b/man/aorsf-package.Rd
index 606da2a8..0c0aa177 100644
--- a/man/aorsf-package.Rd
+++ b/man/aorsf-package.Rd
@@ -8,7 +8,7 @@
 \description{
 \if{html}{\figure{logo.png}{options: style='float: right' alt='logo' width='120'}}
 
-Fit, interpret, and make predictions with oblique random survival forests. Oblique decision trees are notoriously slow compared to their axis based counterparts, but 'aorsf' runs as fast or faster than axis-based decision tree algorithms for right-censored time-to-event outcomes. Methods to accelerate and interpret the oblique random survival forest are described in Jaeger et al., (2023) \doi{ 10.1080/10618600.2023.2231048}.
+Fit, interpret, and make predictions with oblique random survival forests. Oblique decision trees are notoriously slow compared to their axis based counterparts, but 'aorsf' runs as fast or faster than axis-based decision tree algorithms for right-censored time-to-event outcomes. Methods to accelerate and interpret the oblique random survival forest are described in Jaeger et al., (2023) \doi{10.1080/10618600.2023.2231048}.
 }
 \seealso{
 Useful links:
diff --git a/man/orsf.Rd b/man/orsf.Rd
index 60d1de57..0991479e 100644
--- a/man/orsf.Rd
+++ b/man/orsf.Rd
@@ -919,5 +919,5 @@ Ishwaran H, Kogalur UB, Blackstone EH, Lauer MS. Random survival forests. \emph{
 
 Jaeger BC, Long DL, Long DM, Sims M, Szychowski JM, Min YI, Mcclure LA, Howard G, Simon N. Oblique random survival forests. \emph{Annals of applied statistics} 2019 Sep; 13(3):1847-83. DOI: 10.1214/19-AOAS1261
 
-Jaeger BC, Welden S, Lenoir K, Speiser JL, Segar MW, Pandey A, Pajewski NM. Accelerated and interpretable oblique random survival forests. \emph{Journal of Computational and Graphical Statistics} Published online 08 Aug 2023. URL: https://doi.org/10.1080/10618600.2023.2231048
+Jaeger BC, Welden S, Lenoir K, Speiser JL, Segar MW, Pandey A, Pajewski NM. Accelerated and interpretable oblique random survival forests. \emph{Journal of Computational and Graphical Statistics} Published online 08 Aug 2023. DOI: 10.1080/10618600.2023.2231048
 }
diff --git a/man/orsf_control_custom.Rd b/man/orsf_control_custom.Rd
index d2b4b1d7..4aa57cf8 100644
--- a/man/orsf_control_custom.Rd
+++ b/man/orsf_control_custom.Rd
@@ -108,12 +108,7 @@ How well do our two customized ORSFs do? Let’s compute their indices of
 prediction accuracy based on out-of-bag predictions:
 
 \if{html}{\out{<div class="sourceCode r">}}\preformatted{library(riskRegression)
-}\if{html}{\out{</div>}}
-
-\if{html}{\out{<div class="sourceCode">}}\preformatted{## riskRegression version 2023.03.22
-}\if{html}{\out{</div>}}
-
-\if{html}{\out{<div class="sourceCode r">}}\preformatted{library(survival)
+library(survival)
 
 risk_preds <- list(rando = 1 - fit_rando$pred_oobag,
                     pca = 1 - fit_pca$pred_oobag)
diff --git a/man/orsf_vi.Rd b/man/orsf_vi.Rd
index 1f952a6c..9d27d46c 100644
--- a/man/orsf_vi.Rd
+++ b/man/orsf_vi.Rd
@@ -286,5 +286,5 @@ Breiman L. Random forests. \emph{Machine learning} 2001 Oct; 45(1):5-32. DOI: 10
 
 Menze BH, Kelm BM, Splitthoff DN, Koethe U, Hamprecht FA. On oblique random forests. \emph{Joint European Conference on Machine Learning and Knowledge Discovery in Databases} 2011 Sep 4; pp. 453-469. DOI: 10.1007/978-3-642-23783-6_29
 
-Jaeger BC, Welden S, Lenoir K, Speiser JL, Segar MW, Pandey A, Pajewski NM. Accelerated and interpretable oblique random survival forests. \emph{Journal of Computational and Graphical Statistics} Published online 08 Aug 2023. URL: https://doi.org/10.1080/10618600.2023.2231048
+Jaeger BC, Welden S, Lenoir K, Speiser JL, Segar MW, Pandey A, Pajewski NM. Accelerated and interpretable oblique random survival forests. \emph{Journal of Computational and Graphical Statistics} Published online 08 Aug 2023. DOI: 10.1080/10618600.2023.2231048
 }