diff --git a/llama_stack/providers/inline/scoring/meta_reference/__init__.py b/llama_stack/providers/inline/scoring/basic/__init__.py
similarity index 100%
rename from llama_stack/providers/inline/scoring/meta_reference/__init__.py
rename to llama_stack/providers/inline/scoring/basic/__init__.py
diff --git a/llama_stack/providers/inline/scoring/meta_reference/config.py b/llama_stack/providers/inline/scoring/basic/config.py
similarity index 100%
rename from llama_stack/providers/inline/scoring/meta_reference/config.py
rename to llama_stack/providers/inline/scoring/basic/config.py
diff --git a/llama_stack/providers/inline/scoring/meta_reference/scoring.py b/llama_stack/providers/inline/scoring/basic/scoring.py
similarity index 95%
rename from llama_stack/providers/inline/scoring/meta_reference/scoring.py
rename to llama_stack/providers/inline/scoring/basic/scoring.py
index b78379062..ff1ee6c43 100644
--- a/llama_stack/providers/inline/scoring/meta_reference/scoring.py
+++ b/llama_stack/providers/inline/scoring/basic/scoring.py
@@ -70,18 +70,18 @@ class MetaReferenceScoringImpl(Scoring, ScoringFunctionsProtocolPrivate):
         raise NotImplementedError("Register scoring function not implemented yet")
 
     async def validate_scoring_input_dataset_schema(self, dataset_id: str) -> None:
-        dataset_def = await self.datasets_api.get_dataset(dataset_identifier=dataset_id)
-        if not dataset_def.dataset_schema or len(dataset_def.dataset_schema) == 0:
+        dataset_def = await self.datasets_api.get_dataset(dataset_id=dataset_id)
+        if not dataset_def.schema or len(dataset_def.schema) == 0:
             raise ValueError(
                 f"Dataset {dataset_id} does not have a schema defined. Please define a schema for the dataset."
             )
 
         for required_column in ["generated_answer", "expected_answer", "input_query"]:
-            if required_column not in dataset_def.dataset_schema:
+            if required_column not in dataset_def.schema:
                 raise ValueError(
                     f"Dataset {dataset_id} does not have a '{required_column}' column."
                 )
-            if dataset_def.dataset_schema[required_column].type != "string":
+            if dataset_def.schema[required_column].type != "string":
                 raise ValueError(
                     f"Dataset {dataset_id} does not have a '{required_column}' column of type 'string'."
                 )
diff --git a/llama_stack/providers/inline/scoring/meta_reference/scoring_fn/__init__.py b/llama_stack/providers/inline/scoring/basic/scoring_fn/__init__.py
similarity index 100%
rename from llama_stack/providers/inline/scoring/meta_reference/scoring_fn/__init__.py
rename to llama_stack/providers/inline/scoring/basic/scoring_fn/__init__.py
diff --git a/llama_stack/providers/inline/scoring/meta_reference/scoring_fn/base_scoring_fn.py b/llama_stack/providers/inline/scoring/basic/scoring_fn/base_scoring_fn.py
similarity index 100%
rename from llama_stack/providers/inline/scoring/meta_reference/scoring_fn/base_scoring_fn.py
rename to llama_stack/providers/inline/scoring/basic/scoring_fn/base_scoring_fn.py
diff --git a/llama_stack/providers/inline/scoring/meta_reference/scoring_fn/equality_scoring_fn.py b/llama_stack/providers/inline/scoring/basic/scoring_fn/equality_scoring_fn.py
similarity index 100%
rename from llama_stack/providers/inline/scoring/meta_reference/scoring_fn/equality_scoring_fn.py
rename to llama_stack/providers/inline/scoring/basic/scoring_fn/equality_scoring_fn.py
diff --git a/llama_stack/providers/inline/scoring/meta_reference/scoring_fn/fn_defs/__init__.py b/llama_stack/providers/inline/scoring/basic/scoring_fn/fn_defs/__init__.py
similarity index 100%
rename from llama_stack/providers/inline/scoring/meta_reference/scoring_fn/fn_defs/__init__.py
rename to llama_stack/providers/inline/scoring/basic/scoring_fn/fn_defs/__init__.py
diff --git a/llama_stack/providers/inline/scoring/meta_reference/scoring_fn/fn_defs/equality.py b/llama_stack/providers/inline/scoring/basic/scoring_fn/fn_defs/equality.py
similarity index 100%
rename from llama_stack/providers/inline/scoring/meta_reference/scoring_fn/fn_defs/equality.py
rename to llama_stack/providers/inline/scoring/basic/scoring_fn/fn_defs/equality.py
diff --git a/llama_stack/providers/inline/scoring/meta_reference/scoring_fn/fn_defs/llm_as_judge_base.py b/llama_stack/providers/inline/scoring/basic/scoring_fn/fn_defs/llm_as_judge_base.py
similarity index 100%
rename from llama_stack/providers/inline/scoring/meta_reference/scoring_fn/fn_defs/llm_as_judge_base.py
rename to llama_stack/providers/inline/scoring/basic/scoring_fn/fn_defs/llm_as_judge_base.py
diff --git a/llama_stack/providers/inline/scoring/meta_reference/scoring_fn/fn_defs/regex_parser_multiple_choice_answer.py b/llama_stack/providers/inline/scoring/basic/scoring_fn/fn_defs/regex_parser_multiple_choice_answer.py
similarity index 100%
rename from llama_stack/providers/inline/scoring/meta_reference/scoring_fn/fn_defs/regex_parser_multiple_choice_answer.py
rename to llama_stack/providers/inline/scoring/basic/scoring_fn/fn_defs/regex_parser_multiple_choice_answer.py
diff --git a/llama_stack/providers/inline/scoring/meta_reference/scoring_fn/fn_defs/subset_of.py b/llama_stack/providers/inline/scoring/basic/scoring_fn/fn_defs/subset_of.py
similarity index 100%
rename from llama_stack/providers/inline/scoring/meta_reference/scoring_fn/fn_defs/subset_of.py
rename to llama_stack/providers/inline/scoring/basic/scoring_fn/fn_defs/subset_of.py
diff --git a/llama_stack/providers/inline/scoring/meta_reference/scoring_fn/llm_as_judge_scoring_fn.py b/llama_stack/providers/inline/scoring/basic/scoring_fn/llm_as_judge_scoring_fn.py
similarity index 100%
rename from llama_stack/providers/inline/scoring/meta_reference/scoring_fn/llm_as_judge_scoring_fn.py
rename to llama_stack/providers/inline/scoring/basic/scoring_fn/llm_as_judge_scoring_fn.py
diff --git a/llama_stack/providers/inline/scoring/meta_reference/scoring_fn/regex_parser_scoring_fn.py b/llama_stack/providers/inline/scoring/basic/scoring_fn/regex_parser_scoring_fn.py
similarity index 100%
rename from llama_stack/providers/inline/scoring/meta_reference/scoring_fn/regex_parser_scoring_fn.py
rename to llama_stack/providers/inline/scoring/basic/scoring_fn/regex_parser_scoring_fn.py
diff --git a/llama_stack/providers/inline/scoring/meta_reference/scoring_fn/subset_of_scoring_fn.py b/llama_stack/providers/inline/scoring/basic/scoring_fn/subset_of_scoring_fn.py
similarity index 100%
rename from llama_stack/providers/inline/scoring/meta_reference/scoring_fn/subset_of_scoring_fn.py
rename to llama_stack/providers/inline/scoring/basic/scoring_fn/subset_of_scoring_fn.py
diff --git a/llama_stack/providers/inline/scoring/braintrust/braintrust.py b/llama_stack/providers/inline/scoring/braintrust/braintrust.py
index 9105a4978..0a21bc99c 100644
--- a/llama_stack/providers/inline/scoring/braintrust/braintrust.py
+++ b/llama_stack/providers/inline/scoring/braintrust/braintrust.py
@@ -63,18 +63,19 @@ class BraintrustScoringImpl(Scoring, ScoringFunctionsProtocolPrivate):
         )
 
     async def validate_scoring_input_dataset_schema(self, dataset_id: str) -> None:
-        dataset_def = await self.datasets_api.get_dataset(dataset_identifier=dataset_id)
-        if not dataset_def.dataset_schema or len(dataset_def.dataset_schema) == 0:
+        dataset_def = await self.datasets_api.get_dataset(dataset_id=dataset_id)
+        print(dataset_def)
+        if not dataset_def.schema or len(dataset_def.schema) == 0:
             raise ValueError(
                 f"Dataset {dataset_id} does not have a schema defined. Please define a schema for the dataset."
             )
 
         for required_column in ["generated_answer", "expected_answer", "input_query"]:
-            if required_column not in dataset_def.dataset_schema:
+            if required_column not in dataset_def.schema:
                 raise ValueError(
                     f"Dataset {dataset_id} does not have a '{required_column}' column."
                 )
-            if dataset_def.dataset_schema[required_column].type != "string":
+            if dataset_def.schema[required_column].type != "string":
                 raise ValueError(
                     f"Dataset {dataset_id} does not have a '{required_column}' column of type 'string'."
                 )
diff --git a/llama_stack/providers/registry/scoring.py b/llama_stack/providers/registry/scoring.py
index 70f43ad73..1787cac77 100644
--- a/llama_stack/providers/registry/scoring.py
+++ b/llama_stack/providers/registry/scoring.py
@@ -15,8 +15,8 @@ def available_providers() -> List[ProviderSpec]:
             api=Api.scoring,
             provider_type="meta-reference",
             pip_packages=[],
-            module="llama_stack.providers.inline.scoring.meta_reference",
-            config_class="llama_stack.providers.inline.scoring.meta_reference.MetaReferenceScoringConfig",
+            module="llama_stack.providers.inline.scoring.basic",
+            config_class="llama_stack.providers.inline.scoring.basic.MetaReferenceScoringConfig",
             api_dependencies=[
                 Api.datasetio,
                 Api.datasets,