diff --git a/packages/squiggle-lang/__tests__/Distributions/KlDivergence_test.res b/packages/squiggle-lang/__tests__/Distributions/KlDivergence_test.res
index 7d7def74..92786950 100644
--- a/packages/squiggle-lang/__tests__/Distributions/KlDivergence_test.res
+++ b/packages/squiggle-lang/__tests__/Distributions/KlDivergence_test.res
@@ -47,9 +47,6 @@ describe("kl divergence", () => {
       (stdev2 ** 2.0 +. (mean2 -. mean1) ** 2.0) /. (2.0 *. stdev1 ** 2.0) -. 0.5
     let kl = E.R.liftJoin2(klDivergence, prediction, answer)
 
-    // Js.Console.log2("Analytical: ", analyticalKl)
-    // Js.Console.log2("Computed: ", kl)
-
     switch kl {
     | Ok(kl') => kl'->expect->toBeCloseTo(analyticalKl)
     | Error(err) => {
diff --git a/packages/squiggle-lang/__tests__/Distributions/Scale_test.res b/packages/squiggle-lang/__tests__/Distributions/Scale_test.res
index 85622308..d15a0c30 100644
--- a/packages/squiggle-lang/__tests__/Distributions/Scale_test.res
+++ b/packages/squiggle-lang/__tests__/Distributions/Scale_test.res
@@ -3,17 +3,25 @@ open Expect
 open TestHelpers
 
 describe("Scale logarithm", () => {
-  //   test("mean of the base e scalar logarithm of an exponential(10)", () => {
-  //    let rate = 10.0
-  //    let scalelog = DistributionOperation.Constructors.scaleLogarithm(~env, mkExponential(rate), MagicNumbers.Math.e)
-  //
-  //    let meanResult = E.R2.bind(DistributionOperation.Constructors.mean(~env), scalelog)
-  //    let meanAnalytical = Js.Math.log(rate /. MagicNumbers.Math.e)
-  //    switch meanResult {
-  //      | Ok(meanValue) => meanValue -> expect -> toBeCloseTo(meanAnalytical)
-  //      | Error(err) => err -> expect -> toBe(DistributionTypes.OperationError(DivisionByZeroError))
-  //    }
-  //  })
+  /* These tests may not be important, because scalelog isn't normalized
+  The first one may be failing for a number of reasons.
+ */
+  Skip.test("mean of the base e scalar logarithm of an exponential(10)", () => {
+    let rate = 10.0
+    let scalelog = DistributionOperation.Constructors.scaleLogarithm(
+      ~env,
+      mkExponential(rate),
+      MagicNumbers.Math.e,
+    )
+
+    let meanResult = E.R2.bind(DistributionOperation.Constructors.mean(~env), scalelog)
+    // expected value of log of exponential distribution.
+    let meanAnalytical = Js.Math.log(rate) +. 1.0
+    switch meanResult {
+    | Ok(meanValue) => meanValue->expect->toBeCloseTo(meanAnalytical)
+    | Error(err) => err->expect->toBe(DistributionTypes.OperationError(DivisionByZeroError))
+    }
+  })
   let low = 10.0
   let high = 100.0
   let scalelog = DistributionOperation.Constructors.scaleLogarithm(~env, mkUniform(low, high), 2.0)
diff --git a/packages/squiggle-lang/src/rescript/Distributions/PointSetDist/Continuous.res b/packages/squiggle-lang/src/rescript/Distributions/PointSetDist/Continuous.res
index 6b2c8ead..3aca0c66 100644
--- a/packages/squiggle-lang/src/rescript/Distributions/PointSetDist/Continuous.res
+++ b/packages/squiggle-lang/src/rescript/Distributions/PointSetDist/Continuous.res
@@ -271,17 +271,6 @@ module T = Dist({
   let variance = (t: t): float =>
     XYShape.Analysis.getVarianceDangerously(t, mean, Analysis.getMeanOfSquares)
 
-  // let klDivergence0 = (prediction: t, answer: t) => {
-  //   combinePointwise(
-  //     ~combiner=XYShape.PointwiseCombination.combineAlongSupportOfSecondArgument,
-  //     PointSetDist_Scoring.KLDivergence.integrand,
-  //     prediction,
-  //     answer,
-  //   )
-  //   |> E.R.fmap(shapeMap(XYShape.T.filterYValues(Js.Float.isFinite)))
-  //   |> E.R.fmap(integralEndY)
-  // }
-
   let klDivergence = (prediction: t, answer: t) => {
     let newShape = XYShape.PointwiseCombination.combineAlongSupportOfSecondArgument(
       PointSetDist_Scoring.KLDivergence.integrand,
diff --git a/packages/squiggle-lang/src/rescript/Utility/XYShape.res b/packages/squiggle-lang/src/rescript/Utility/XYShape.res
index 295865f8..840729f2 100644
--- a/packages/squiggle-lang/src/rescript/Utility/XYShape.res
+++ b/packages/squiggle-lang/src/rescript/Utility/XYShape.res
@@ -390,7 +390,9 @@ module PointwiseCombination = {
       }
     `)
 
-  // This function is used for kl divergence
+  /*
+    This is from an approach to kl divergence that was ultimately rejected. Leaving it in for now because it may help us factor `combine` out of raw javascript soon.
+ */
   let combineAlongSupportOfSecondArgument0: (
     (float, float) => result<float, Operation.Error.t>,
     interpolator,
@@ -450,7 +452,6 @@ module PointwiseCombination = {
         }
       | None => ()
       }
-      // Js.Console.log(newYs)
     }
     T.filterOkYs(newXs, newYs)->Ok
   }
@@ -489,6 +490,7 @@ module PointwiseCombination = {
     result
   }
 
+  // This function is used for klDivergence
   let combineAlongSupportOfSecondArgument: (
     (float, float) => result<float, Operation.Error.t>,
     T.t,
diff --git a/packages/squiggle-lang/tsconfig.json b/packages/squiggle-lang/tsconfig.json
index 7a610d10..2ac0d8bf 100644
--- a/packages/squiggle-lang/tsconfig.json
+++ b/packages/squiggle-lang/tsconfig.json
@@ -15,5 +15,10 @@
   },
   "target": "ES6",
   "include": ["src/**/*"],
-  "exclude": ["node_modules", "**/*.spec.ts", "webpack.config.js"]
+  "exclude": [
+    "../../node_modules",
+    "node_modules",
+    "**/*.spec.ts",
+    "webpack.config.js"
+  ]
 }