Error code:   StreamingRowsError
Exception:    TypeError
Message:      Couldn't cast array of type
struct<target_mass_at_prediction: double, uniform_accuracy_baseline: double, fixed_answer_accuracy_baseline: double, baseline_adjusted_skill: double, baseline_adjusted_score: double>
to
{'binary_brier': Value('float64'), 'accuracy': Value('float64'), 'positive_recall': Value('float64'), 'specificity': Value('float64'), 'precision': Value('float64'), 'balanced_accuracy': Value('float64'), 'f1': Value('float64'), 'true_positive': Value('float64'), 'false_positive': Value('float64'), 'false_negative': Value('float64'), 'true_negative': Value('float64'), 'positive_prevalence': Value('float64'), 'majority_accuracy_baseline': Value('float64'), 'constant_brier_baseline': Value('float64'), 'brier_skill': Value('float64'), 'baseline_adjusted_skill': Value('float64'), 'baseline_adjusted_score': Value('float64')}
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2951, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2312, in cast_table_to_schema
                  cast_array_to_feature(
                  ~~~~~~~~~~~~~~~~~~~~~^
                      table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                      feature,
                      ^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1861, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                                           ~~~~^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2158, in cast_array_to_feature
                  raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
              TypeError: Couldn't cast array of type
              struct<target_mass_at_prediction: double, uniform_accuracy_baseline: double, fixed_answer_accuracy_baseline: double, baseline_adjusted_skill: double, baseline_adjusted_score: double>
              to
              {'binary_brier': Value('float64'), 'accuracy': Value('float64'), 'positive_recall': Value('float64'), 'specificity': Value('float64'), 'precision': Value('float64'), 'balanced_accuracy': Value('float64'), 'f1': Value('float64'), 'true_positive': Value('float64'), 'false_positive': Value('float64'), 'false_negative': Value('float64'), 'true_negative': Value('float64'), 'positive_prevalence': Value('float64'), 'majority_accuracy_baseline': Value('float64'), 'constant_brier_baseline': Value('float64'), 'brier_skill': Value('float64'), 'baseline_adjusted_skill': Value('float64'), 'baseline_adjusted_score': Value('float64')}