diff --git a/configs/data/dataset.yaml b/configs/data/dataset.yaml
index 7299c1d3..1f2e0cd8 100644
--- a/configs/data/dataset.yaml
+++ b/configs/data/dataset.yaml
@@ -14,8 +14,8 @@ dataset:
     test_split_filename: "split_mapping/test_split.csv"
     tiling_run_id: "fdf7550a2004474f8c7a05dc0cf1fd86"
     filter_tiles_run_id: "9a844082b48d47bfa5d3e7a37d7de268"
-    stratified_kfold_run_id: "850c81506684450b9af92296acfd045a"
-    stratified_group_kfold_run_id: "382b41d2fa894514908e8067949c4326"
+    stratified_kfold_run_id: "e2132cd681e04892b2bfe837a7295b55"
+    stratified_group_kfold_run_id: "9c2618576b89453893788a7401fef393"
     embedding_run_ids:
       virchow2: "262d680f52374614baaf19f1e4d05940"
       provgigapath: "5099ce57e886411dababfc1234a88b23"
diff --git a/configs/experiment/ml/final_linear_provgigapath_adamw.yaml b/configs/experiment/ml/final_linear_provgigapath_adamw.yaml
index fb54dc66..6319e25b 100644
--- a/configs/experiment/ml/final_linear_provgigapath_adamw.yaml
+++ b/configs/experiment/ml/final_linear_provgigapath_adamw.yaml
@@ -7,8 +7,6 @@ defaults:
 embedding_model_name: ProvGigaPath
 embedding_dim: 1536
 embedding_run_id: ${dataset.mlflow_artifacts.embedding_run_ids.provgigapath}
-kfold_strategy: stratified_group
-kfold_run_id: ${dataset.mlflow_artifacts.stratified_group_kfold_run_id}
 mlflow_artifact_path: linear_classifier_final_provgigapath
 
 # Set after Stage 1 from ProvGigaPath's own AdamW sweep selected by
diff --git a/configs/experiment/ml/final_linear_provgigapath_lbfgs.yaml b/configs/experiment/ml/final_linear_provgigapath_lbfgs.yaml
index 85c81719..8481053b 100644
--- a/configs/experiment/ml/final_linear_provgigapath_lbfgs.yaml
+++ b/configs/experiment/ml/final_linear_provgigapath_lbfgs.yaml
@@ -7,8 +7,6 @@ defaults:
 embedding_model_name: ProvGigaPath
 embedding_dim: 1536
 embedding_run_id: ${dataset.mlflow_artifacts.embedding_run_ids.provgigapath}
-kfold_strategy: stratified_group
-kfold_run_id: ${dataset.mlflow_artifacts.stratified_group_kfold_run_id}
 mlflow_artifact_path: linear_classifier_final_provgigapath
 
 # Set after Stage 1 from ProvGigaPath's own LBFGS sweep selected by
diff --git a/configs/experiment/ml/train_linear_virchow2_adamw_group_kfold.yaml b/configs/experiment/ml/train_linear_virchow2_adamw_group_kfold.yaml
index 86f56479..8f342d0e 100644
--- a/configs/experiment/ml/train_linear_virchow2_adamw_group_kfold.yaml
+++ b/configs/experiment/ml/train_linear_virchow2_adamw_group_kfold.yaml
@@ -4,9 +4,6 @@ defaults:
   - /ml/task: kfold_linear_classifier
   - _self_
 
-kfold_strategy: stratified_group
-kfold_run_id: ${dataset.mlflow_artifacts.stratified_group_kfold_run_id}
-
 model:
   optimizer: adamw
   learning_rate: 1.0e-4
diff --git a/configs/ml/task/final_linear_classifier.yaml b/configs/ml/task/final_linear_classifier.yaml
index a33638e0..be6189fd 100644
--- a/configs/ml/task/final_linear_classifier.yaml
+++ b/configs/ml/task/final_linear_classifier.yaml
@@ -13,8 +13,12 @@ mode: fit
 embedding_model_name: Virchow2
 embedding_dim: 2560
 embedding_run_id: ${dataset.mlflow_artifacts.embedding_run_ids.virchow2}
-kfold_strategy: stratified
-kfold_run_id: ${dataset.mlflow_artifacts.stratified_kfold_run_id}
+# stratified_group is the default: plain stratified splits tiles from one slide
+# across folds, so validation scores are inflated by slide-level leakage. The two
+# fields must stay in sync — kfold_strategy only labels the run, kfold_run_id picks
+# the data. To use plain stratified folds, override both.
+kfold_strategy: stratified_group
+kfold_run_id: ${dataset.mlflow_artifacts.stratified_group_kfold_run_id}
 filter_tiles_run_id: ${dataset.mlflow_artifacts.filter_tiles_run_id}
 
 train_embedding_uri: runs:/${embedding_run_id}/train/tiles
diff --git a/configs/ml/task/kfold_linear_classifier.yaml b/configs/ml/task/kfold_linear_classifier.yaml
index dd0a05d0..06166be0 100644
--- a/configs/ml/task/kfold_linear_classifier.yaml
+++ b/configs/ml/task/kfold_linear_classifier.yaml
@@ -13,8 +13,12 @@ mode: fit
 embedding_model_name: Virchow2
 embedding_dim: 2560
 embedding_run_id: ${dataset.mlflow_artifacts.embedding_run_ids.virchow2}
-kfold_strategy: stratified
-kfold_run_id: ${dataset.mlflow_artifacts.stratified_kfold_run_id}
+# stratified_group is the default: plain stratified splits tiles from one slide
+# across folds, so validation scores are inflated by slide-level leakage. The two
+# fields must stay in sync — kfold_strategy only labels the run, kfold_run_id picks
+# the data. To use plain stratified folds, override both.
+kfold_strategy: stratified_group
+kfold_run_id: ${dataset.mlflow_artifacts.stratified_group_kfold_run_id}
 filter_tiles_run_id: ${dataset.mlflow_artifacts.filter_tiles_run_id}
 
 train_embedding_uri: runs:/${embedding_run_id}/train/tiles