Merge pull request #115 from ContextLab/revision-4

post-acceptance revisions for Nature Communications

Author: paxtonfitzpatrick

.gitignore

@@ -37,6 +37,7 @@ exp/server.log
 # latex extensions
 paper/**/*.aux
 paper/**/*.fdb_latexmk
+paper/**/*.fff
 paper/**/*.fls
 paper/**/*.log
 paper/**/*.out
@@ -45,3 +46,6 @@ paper/**/*.blg
 paper/**/*.bbl
 texput.log
 paper/.#compile.sh
+
+# MS Word temp files
+paper/**/~$*

README.md

@@ -1,4 +1,4 @@
-# Text embedding models yield high-resolution insights into conceptual knowledge from short multiple-choice quizzes
+# Text embedding models yield detailed conceptual knowledge maps derived from short multiple-choice quizzes
 
 <p align="center">
   <a href="https://psyarxiv.com/dh3q2">
@@ -7,8 +7,8 @@
 </p>
 
 This repository contains all data and code used to produce the paper
-"[_Text embedding models yield high-resolution insights into conceptual
-knowledge from short multiple-choice quizzes_](https://psyarxiv.com/dh3q2)" by
+"[_Text embedding models yield detailed conceptual
+knowledge maps derived from short multiple-choice quizzes_](https://psyarxiv.com/dh3q2)" by
 Paxton C. Fitzpatrick, Andrew C. Heusser, and Jeremy R. Manning.
 
 We also include reproducible environments for running our experiment and
@@ -17,7 +17,7 @@ analyses via [Docker](https://www.docker.com/).
 
 ## Table of Contents
 
-- [Text embedding models yield high-resolution insights into conceptual knowledge from short multiple-choice quizzes](#text-embedding-models-yield-high-resolution-insights-into-conceptual-knowledge-from-short-multiple-choice-quizzes)
+- [Text embedding models yield detailed conceptual knowledge maps derived from short multiple-choice quizzes](#text-embedding-models-yield-detailed-conceptual-knowledge-maps-derived-from-short-multiple-choice-quizzes)
   - [Table of Contents](#table-of-contents)
   - [Repo Organization](#repo-organization)
   - [Installing Docker](#installing-docker)

code/notebooks/main/4_reconstructing-knowledge.ipynb

@@ -121,7 +121,7 @@
     "        A `pandas.Series` whose values are iterables of length 2 \n",
     "        representing lower and upper confidence interval bounds for the \n",
     "        accross-participants mean overall/raw p(correct) for each quiz.\n",
-    "    interp_func : float, optional\n",
+    "    interp_freq : float, optional\n",
     "        If provided, interpolate the series of by-distance p(correct)\n",
     "        values for each quiz & accuracy of reference question to the \n",
     "        given frequency before computing the intersections.\n",
@@ -1296,7 +1296,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.7"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,