The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ValueError
Message: Expected object or value
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 291, in _generate_tables
pa_table = paj.read_json(
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
)
File "pyarrow/_json.pyx", line 364, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: JSON parse error: Column() changed from object to string in row 0
During handling of the above exception, another exception occurred:
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 544, 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 3052, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 527, in __iter__
yield from self.ex_iterable
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in __iter__
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 306, in _generate_tables
batch = json_encode_fields_in_json_lines(original_batch, json_field_paths)
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 111, in json_encode_fields_in_json_lines
examples = [ujson_loads(line) for line in original_batch.splitlines()]
~~~~~~~~~~~^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 20, in ujson_loads
return pd.io.json.ujson_loads(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
ValueError: Expected object or valueNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
AI4Sci brain-computer-interface decoding: public tracks
Prepared data for three of the five tracks of the brain-computer-interface-decoding task in
T0-RSI/ai4sci-tasks and
sunnweiwei/science-speedrun. Each was built by
the task's environment/data/materialize.py from pinned public sources:
| track | source | classes | shape (channels, seconds, 200 Hz) | train / val / test windows |
|---|---|---|---|---|
ad65 |
OpenNeuro ds004504 derivatives (CC0) | 3: Alzheimer's, frontotemporal dementia, control | 19 × 10 × 200 | 3,774 / 1,343 / 1,376 |
openbmi |
GigaDB 100542 motor-imagery sessions (CC0) | 2: left, right | 62 × 4 × 200 | 12,800 / 4,400 / 4,400 |
longitudinal |
OpenNeuro ds007176 (CC0) | 2: eyes closed, open | 58 × 2 × 200 | 28,523 / 8,418 / 10,028 |
Subjects are split with seed 3407 (test 20%, then validation 25% of the rest; AD65 stratified by diagnosis); every session stays with its subject. Arrays are float32 microvolts in NumPy shards.
runtime/development/<track>/{train,val}/ manifest.json (id, label, subject, session, path, index), shards
runtime/private/<track>/public/ test inputs: manifest without labels, shards in random order
runtime/private/<track>/truth.jsonl test labels, subjects and sessions (verifier only)
records/<track>/ subject splits, preprocessing statistics, build receipt
release-manifest.json size and SHA-256 of every file
The FACED and TUEV tracks are not redistributable and come from a separate controlled-access
release. The task's environment/data/materialize.sh release ROOT installs all five tracks and
verifies every file against release-manifest.json. Only runtime/development may be mounted
into an agent's workspace; runtime/private is for the verifier.
Citations: Miltiadous et al. (2023), Data 8(6), 95 (ds004504); Lee et al. (2019), GigaScience 8(5), giz002 (OpenBMI); OpenNeuro ds007176.
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