Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
patient_id: string
disease_area: string
condition_label: string
time_unit: string
timepoints: list<item: int64>
child 0, item: int64
variables: list<item: struct<name: string, unit: string, values: list<item: double>>>
child 0, item: struct<name: string, unit: string, values: list<item: double>>
child 0, name: string
child 1, unit: string
child 2, values: list<item: double>
child 0, item: double
intervention: struct<present: bool, type: string, start_time: int64, dose_schedule_known: bool>
child 0, present: bool
child 1, type: string
child 2, start_time: int64
child 3, dose_schedule_known: bool
outcomes: struct<survival_days: int64, response_label: string, trajectory_complete: bool>
child 0, survival_days: int64
child 1, response_label: string
child 2, trajectory_complete: bool
tasks: list<item: struct<name: string, goal: string, minimum_requirements: list<item: string>>>
child 0, item: struct<name: string, goal: string, minimum_requirements: list<item: string>>
child 0, name: string
child 1, goal: string
child 2, minimum_requirements: list<item: string>
child 0, item: string
to
{'tasks': List({'name': Value('string'), 'goal': Value('string'), 'minimum_requirements': List(Value('string'))})}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
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 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 289, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 124, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
patient_id: string
disease_area: string
condition_label: string
time_unit: string
timepoints: list<item: int64>
child 0, item: int64
variables: list<item: struct<name: string, unit: string, values: list<item: double>>>
child 0, item: struct<name: string, unit: string, values: list<item: double>>
child 0, name: string
child 1, unit: string
child 2, values: list<item: double>
child 0, item: double
intervention: struct<present: bool, type: string, start_time: int64, dose_schedule_known: bool>
child 0, present: bool
child 1, type: string
child 2, start_time: int64
child 3, dose_schedule_known: bool
outcomes: struct<survival_days: int64, response_label: string, trajectory_complete: bool>
child 0, survival_days: int64
child 1, response_label: string
child 2, trajectory_complete: bool
tasks: list<item: struct<name: string, goal: string, minimum_requirements: list<item: string>>>
child 0, item: struct<name: string, goal: string, minimum_requirements: list<item: string>>
child 0, name: string
child 1, goal: string
child 2, minimum_requirements: list<item: string>
child 0, item: string
to
{'tasks': List({'name': Value('string'), 'goal': Value('string'), 'minimum_requirements': List(Value('string'))})}
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.
Confluence Longitudinal Benchmark Spec
This repository is a public benchmark specification for packaging longitudinal biomedical data into the Project Confluence ecosystem.
It is not a patient dataset. It contains:
- a schema for longitudinal cohort packaging
- synthetic example records
- benchmark task definitions
- documentation for intended and out-of-scope use
Intended Use
This asset is designed to help:
- standardize public dataset ingestion
- benchmark trajectory-readiness of candidate datasets
- support reproducible, non-clinical research workflows in Confluence
Out-Of-Scope Use
This asset must not be used as:
- a clinical dataset
- a substitute for patient-level validation
- a medical decision system
Files
schema/longitudinal_benchmark_schema.json: canonical schemadata/sample_records.jsonl: synthetic examplesbenchmark_tasks.json: benchmark tasks and scoring targets
Provenance
All records in this starter asset are synthetic and safe for public release.
Citation
Use the main Project Confluence citation until a dedicated benchmark citation is published.
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