The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
row_count: int64
columns: list<item: struct<name: string, dtype: string>>
child 0, item: struct<name: string, dtype: string>
child 0, name: string
child 1, dtype: string
datasets: struct<synthetic: struct<paper_core_rows: int64, public_rows: int64, actual_research_rows_shared: in (... 263 chars omitted)
child 0, synthetic: struct<paper_core_rows: int64, public_rows: int64, actual_research_rows_shared: int64>
child 0, paper_core_rows: int64
child 1, public_rows: int64
child 2, actual_research_rows_shared: int64
child 1, support2: struct<source_rows: int64, paper_evaluation_rows: int64, public_mock_rows: int64, actual_clinical_ro (... 17 chars omitted)
child 0, source_rows: int64
child 1, paper_evaluation_rows: int64
child 2, public_mock_rows: int64
child 3, actual_clinical_rows_shared: int64
child 2, mimic_iv: struct<paper_cohort_rows: int64, paper_test_rows: int64, public_mock_rows: int64, actual_clinical_ro (... 17 chars omitted)
child 0, paper_cohort_rows: int64
child 1, paper_test_rows: int64
child 2, public_mock_rows: int64
child 3, actual_clinical_rows_shared: int64
contains_real_clinical_rows: bool
release_type: string
to
{'release_type': Value('string'), 'contains_real_clinical_rows': Value('bool'), 'datasets': {'synthetic': {'paper_core_rows': Value('int64'), 'public_rows': Value('int64'), 'actual_research_rows_shared': Value('int64')}, 'support2': {'source_rows': Value('int64'), 'paper_evaluation_rows': Value('int64'), 'public_mock_rows': Value('int64'), 'actual_clinical_rows_shared': Value('int64')}, 'mimic_iv': {'paper_cohort_rows': Value('int64'), 'paper_test_rows': Value('int64'), 'public_mock_rows': Value('int64'), 'actual_clinical_rows_shared': Value('int64')}}}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, 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 129, 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 489, 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 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, 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 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, 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 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
row_count: int64
columns: list<item: struct<name: string, dtype: string>>
child 0, item: struct<name: string, dtype: string>
child 0, name: string
child 1, dtype: string
datasets: struct<synthetic: struct<paper_core_rows: int64, public_rows: int64, actual_research_rows_shared: in (... 263 chars omitted)
child 0, synthetic: struct<paper_core_rows: int64, public_rows: int64, actual_research_rows_shared: int64>
child 0, paper_core_rows: int64
child 1, public_rows: int64
child 2, actual_research_rows_shared: int64
child 1, support2: struct<source_rows: int64, paper_evaluation_rows: int64, public_mock_rows: int64, actual_clinical_ro (... 17 chars omitted)
child 0, source_rows: int64
child 1, paper_evaluation_rows: int64
child 2, public_mock_rows: int64
child 3, actual_clinical_rows_shared: int64
child 2, mimic_iv: struct<paper_cohort_rows: int64, paper_test_rows: int64, public_mock_rows: int64, actual_clinical_ro (... 17 chars omitted)
child 0, paper_cohort_rows: int64
child 1, paper_test_rows: int64
child 2, public_mock_rows: int64
child 3, actual_clinical_rows_shared: int64
contains_real_clinical_rows: bool
release_type: string
to
{'release_type': Value('string'), 'contains_real_clinical_rows': Value('bool'), 'datasets': {'synthetic': {'paper_core_rows': Value('int64'), 'public_rows': Value('int64'), 'actual_research_rows_shared': Value('int64')}, 'support2': {'source_rows': Value('int64'), 'paper_evaluation_rows': Value('int64'), 'public_mock_rows': Value('int64'), 'actual_clinical_rows_shared': Value('int64')}, 'mimic_iv': {'paper_cohort_rows': Value('int64'), 'paper_test_rows': Value('int64'), 'public_mock_rows': Value('int64'), 'actual_clinical_rows_shared': Value('int64')}}}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
ActionAudit Public Data Companion
This repository contains independently generated demonstration data for the ActionAudit reproducibility package.
It contains no actual SUPPORT2 or MIMIC-IV patient rows.
Directories
synthetic/
The project's core Phase 0 synthetic benchmark contained 5,000 generated records.
This public file contains 500 independently generated demonstration rows.
The sample illustrates the prediction, outcome, observation, action, and timing interfaces. It is not the frozen row-level cohort used to calculate the paper's reported numerical estimates.
support2_interface_mock/
The SUPPORT2 source contains 9,105 patient records.
The frozen ActionAudit evaluation split contained 1,821 patients and used a 60-day mortality horizon.
This directory contains 182 independently generated mock rows. The row count is approximately 10% of the frozen evaluation split.
Actual SUPPORT2 patient records shared here: 0.
Researchers seeking empirical reproduction should obtain SUPPORT2 from its authorized provider and run the public preprocessing scripts.
mimic_iv_interface_mock/
The frozen ActionAudit MIMIC-IV cohort contained 155,059 admissions. The test split contained 31,012 admissions and used a 30-day mortality horizon.
This directory contains 3,101 independently generated mock rows. The row count is approximately 10% of the frozen test split.
Actual MIMIC-IV admissions shared here: 0.
Researchers seeking empirical reproduction must obtain credentialed MIMIC-IV access through PhysioNet and accept the applicable data-use agreement.
What the interface samples can do
The samples can be used to:
- inspect expected column names;
- test file loading;
- develop data adapters;
- test simple analysis code;
- understand the ActionAudit data interface.
They cannot reproduce the clinical estimates reported in the paper.
Important distinction
These files are not:
- subsamples of the clinical datasets;
- anonymized clinical rows;
- transformed clinical values;
- patient-level predictions from the paper;
- statistical replicas intended to preserve real patient distributions.
They are newly generated demonstration records.
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