diff --git a/index.ipynb b/index.ipynb
index 0d57bdd..e605c7f 100644
--- a/index.ipynb
+++ b/index.ipynb
@@ -20,9 +20,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "trusted": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "%matplotlib widget\n",
@@ -40,9 +38,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "trusted": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Input/output options\n",
@@ -59,9 +55,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "trusted": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Set debug to the global parameter \n",
@@ -75,9 +69,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "trusted": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -119,9 +111,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "trusted": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -157,9 +147,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {
-    "trusted": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -196,9 +184,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "metadata": {
-    "trusted": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "#First, find the color card. You won't see any output of this function. \n",
@@ -209,9 +195,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "metadata": {
-    "trusted": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "#Make a color card matrix \n",
@@ -222,9 +206,7 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "metadata": {
-    "trusted": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Define the standard color card matrix, we know what the colors of those chips should be in a \"perfect\" image, so we will correct to those values\n",
@@ -236,7 +218,8 @@
     "        #        pos = 0: bottom-left corner\n",
     "        #        pos = 1: bottom-right corner\n",
     "        #        pos = 2: top-right corner\n",
-    "        #        pos = 3: top-left corner\n",
+    "        #        pos = 3: top-left corner (or following pcv.transform.detect_color_card)\n",
+    "        #        Note, using pcv.transform.detect_color_card orders the color card mask and should always use `pos = 3`\n",
     "\n",
     "std_color_matrix = pcv.transform.std_color_matrix (pos=3)"
    ]
@@ -244,9 +227,7 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "metadata": {
-    "trusted": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -285,9 +266,7 @@
   {
    "cell_type": "code",
    "execution_count": 37,
-   "metadata": {
-    "trusted": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -330,9 +309,7 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "metadata": {
-    "trusted": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "#If you want to save your color corrected image, do so here. Do NOT save over your raw image. \n",
@@ -344,9 +321,7 @@
   {
    "cell_type": "code",
    "execution_count": 21,
-   "metadata": {
-    "trusted": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -384,9 +359,7 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "metadata": {
-    "trusted": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "#Threshold your image by choosing points in the plot that will separate the green plant pixels from everything else. \n",
@@ -398,9 +371,7 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "metadata": {
-    "trusted": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -439,9 +410,7 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "metadata": {
-    "trusted": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -487,9 +456,7 @@
   {
    "cell_type": "code",
    "execution_count": 25,
-   "metadata": {
-    "trusted": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -533,9 +500,7 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "metadata": {
-    "trusted": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -580,8 +545,7 @@
    "cell_type": "code",
    "execution_count": 27,
    "metadata": {
-    "scrolled": true,
-    "trusted": true
+    "scrolled": true
    },
    "outputs": [
     {
@@ -629,9 +593,7 @@
   {
    "cell_type": "code",
    "execution_count": 28,
-   "metadata": {
-    "trusted": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -730,8 +692,7 @@
    "cell_type": "code",
    "execution_count": 29,
    "metadata": {
-    "scrolled": true,
-    "trusted": true
+    "scrolled": true
    },
    "outputs": [],
    "source": [
@@ -754,9 +715,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "trusted": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": []
   }
@@ -777,7 +736,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.14"
+   "version": "3.11.12"
   }
  },
  "nbformat": 4,