diff --git a/CHANGELOG.md b/CHANGELOG.md
index 55e9ee63..b1d08aa7 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -26,6 +26,8 @@
 
 * `process_dataset`: Add the `--seed` argument the API and README already advertised, and pass it through from the `process_datasets` workflow. Without it `par$seed` was `NULL`, and `set.seed(NULL)` re-seeds from the clock -- so the test-cell and ATAC-peak subsampling were not reproducible (PR #27).
 
+* `novel`: Record every all-zero training feature in `uns["removed_vars"]`, not just the first. With more than one such feature, `novel_predict` left extra columns in the test matrix and the model dimensions no longer lined up (PR #33).
+
 # task_predict_modality 0.1.1
 
 ## NEW FUNCTIONALITY
diff --git a/src/methods/novel/novel_train/script.py b/src/methods/novel/novel_train/script.py
index 0cd94124..4b24f527 100644
--- a/src/methods/novel/novel_train/script.py
+++ b/src/methods/novel/novel_train/script.py
@@ -150,7 +150,7 @@
 # Add model dim for use in predict part
 adata.uns["model_dim"] = {"mod1": n_vars_mod1, "mod2": n_vars_mod2}
 if rem_var is not None:
-  adata.uns["removed_vars"] = [rem_var[0]]
+  adata.uns["removed_vars"] = list(rem_var)
 adata.write_h5ad(output_h5ad, compression="gzip")
 
 if mod1 != 'ADT':