diff --git a/nimare/annotate/gclda.py b/nimare/annotate/gclda.py
index 7e8a70626..940c2459b 100755
--- a/nimare/annotate/gclda.py
+++ b/nimare/annotate/gclda.py
@@ -179,7 +179,7 @@ def __init__(
 
         # Create docidx column
         count_df["docidx"] = count_df["id"].map(docidx_mapper)
-        count_df = count_df.drop("id", 1)
+        count_df = count_df.drop(columns=["id"])
 
         # Remove words not found anywhere in the corpus
         n_terms = len(count_df.columns) - 1  # number of columns minus one for docidx
diff --git a/nimare/annotate/text.py b/nimare/annotate/text.py
index 5f9f71feb..5aaac04f2 100755
--- a/nimare/annotate/text.py
+++ b/nimare/annotate/text.py
@@ -59,7 +59,15 @@ def generate_counts(text_df, text_column="abstract", tfidf=True, min_df=50, max_
             stop_words=stop_words,
         )
     weights = vectorizer.fit_transform(text).toarray()
-    names = vectorizer.get_feature_names()
+
+    if hasattr(vectorizer, "get_feature_names_out"):
+        # scikit-learn >= 1.0.0
+        names = vectorizer.get_feature_names_out()
+    else:
+        # scikit-learn < 1.0.0
+        # To remove when we drop support for 3.6 and increase minimum sklearn version to 1.0.0.
+        names = vectorizer.get_feature_names()
+
     names = [str(name) for name in names]
     weights_df = pd.DataFrame(weights, columns=names, index=ids)
     weights_df.index.name = "id"
diff --git a/nimare/tests/utils.py b/nimare/tests/utils.py
index 1e6c5c97d..ecc74cf4a 100644
--- a/nimare/tests/utils.py
+++ b/nimare/tests/utils.py
@@ -87,7 +87,7 @@ def _check_p_values(
         for j in range(3)
     ]
 
-    best_chance_p_values = p_map[gtf_idx]
+    best_chance_p_values = p_map[tuple(gtf_idx)]
     assert all(best_chance_p_values < ALPHA) == good_sensitivity
 
     p_array_sig = p_array[sig_idx]
diff --git a/pyproject.toml b/pyproject.toml
index 6d09d30ce..456cb6d10 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -26,7 +26,9 @@ exclude = '''
 
 [tool.pytest.ini_options]
 markers = [
-    "performance: mark tests that measure performance (deselect with '-m \"not performance\"')",
+    "performance_smoke: mark smoke tests that measure performance",
+    "performance_estimators: mark tests that measure estimator performance",
+    "performance_correctors: mark tests that measure corrector performance",
 ]
 
 [tool.isort]