diff --git a/README.md b/README.md
index a9289dd6..0a0fb8c5 100644
--- a/README.md
+++ b/README.md
@@ -5,10 +5,10 @@
 
 # DSCIM: The Data-driven Spatial Climate Impact Model
 
-This Python library enables the calculation of sector-specific partial social cost of greenhouse gases (SC-GHG) and SCGHGs that are combined across sectors using a variety of valuation methods and assumptions. The main purpose of this
+This Python library enables the calculation of sector-specific partial social cost of greenhouse gases (SC-GHG) and SC-GHGs that are combined across sectors using a variety of valuation methods and assumptions. The main purpose of this
 library is to parse the monetized spatial damages from different sectors and integrate them
 using different options ("menu options") that encompass different decisions, such as
-discount levels, discount strategies, and different considerations related to
+discount levels, discount strategies, and different considerations related to valuing
 economic and climate uncertainty. 
 
 ## Installation
@@ -63,10 +63,10 @@ SubGraph1Flow(Storage and I/O)
   end
 
   subgraph "Recipe Book"
-  A[StackedDamages] --> B[MainMenu]
-  B[MainMenu] --> C[AddingUpRecipe];
-  B[MainMenu] --> D[RiskAversionRecipe];
-  B[MainMenu] --> E[EquityRecipe]
+  A[StackedDamages] --> B[MainRecipe]
+  B[MainRecipe] --> C[Baseline];
+  B[MainRecipe] --> D[RiskAversionRecipe];
+  B[MainRecipe] --> E[EquityRecipe]
 end
 ```
 
@@ -84,7 +84,7 @@ Class            | Function
 
 
 and these elements can be used for the menu options: 
- - `AddingUpRecipe`: Adding up all damages and collapse them to calculate a general SCC without valuing uncertainty.
+ - `Baseline`: Adding up all damages and collapse them to calculate SC-GHGs without valuing climate or economic uncertainty.
  - `RiskAversionRecipe`: Add risk aversion certainty equivalent to consumption calculations - Value uncertainty over econometric and climate draws.
  - `EquityRecipe`: Add risk aversion and equity to the consumption calculations. Equity includes taking a certainty equivalent over spatial impact regions.