The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ArrowInvalid
Message: JSON parse error: Invalid value. in row 0
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 342, in _generate_tables
df = pandas_read_json(f)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
return pd.read_json(path_or_buf, **kwargs)
~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 815, in read_json
return json_reader.read()
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1014, in read
obj = self._get_object_parser(self.data)
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1040, in _get_object_parser
obj = FrameParser(json, **kwargs).parse()
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1176, in parse
self._parse()
~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1392, in _parse
ujson_loads(json, precise_float=self.precise_float), dtype=None
~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ValueError: Expected object or value
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 2559, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, 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 558, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, 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 345, in _generate_tables
raise e
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: Invalid value. in row 0Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
DVIDIA | PiPER probe evidence v0.1
Simulation-only authored short-lift/hold research on 12 fixed synthetic scenes, once per controller (24 attempts). Independent reconstruction checked 480,000 native 1 ms rows. Evidence gate: 6 admissions, 0/6 false initial qualifications; four later hold losses, final 2/12 qualified. Timer: 12 admissions, 8/12 false initial qualifications; final 2/12 qualified. Closed-loop trajectories can differ. These counts do not establish general accuracy, speed or hardware safety.
The historical learned 5/12 placement result is unchanged. No training, model weights, full transport/placement or physical sensor qualification is included. The 10 N per-finger ceiling is an arbitrary synthetic assumption, not calibration.
Paths under study/ preserve every frozen study artifact. Paths under audit/ preserve the independent original audit and its receipt, plus a guarded normal- mode reanalysis. The original audit used assertions and was executed with normal Python. Always use tools/audit_guarded.py for reuse: it refuses -O/-OO and pins the original script. The guarded reanalysis was byte-identical to the original.
After checking the release ZIP checksum, copy tools/verify_archive.py from the ZIP or reviewed repository and verify/reconstruct it with standard Python:
python verify_archive.py piper-probe-evidence-v01.zip --output evidence
With the project dependencies and frozen checkout available, re-read the saved records (no physics rerun), writing new outputs outside the archived study:
python evidence/tools/audit_guarded.py --audit-script evidence/audit/audit.py --guard-receipt new-guard.json --study evidence/study --repo /path/to/frozen-checkout --output new-audit.json
Frozen source: https://github.com/Dvidia-Inference/dvidia-training/tree/a6a1d15db905214da52eb3942ebead3f85254762 Research article (publication target): https://research.dvidia.org/papers/piper-probe-evidence-v01/ Source release (publication target): https://github.com/Dvidia-Inference/dvidia-training/releases/tag/piper-probe-evidence-v0.1-preview Evidence dataset (publication target): https://huggingface.co/datasets/Dvidia/piper-probe-evidence-v01
Original DVIDIA code and authored synthetic records are MIT. Upstream notices remain included. No robot meshes, simulator binaries or credentials are bundled. DVIDIA research: https://research.dvidia.org | hello@dvidia.org
Archive SHA-256: 9ac7ab4167a9aea703b69f93e8fde4771777950eec272420249291a108d3fb8e
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