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
schema: string
as_of: timestamp[s]
note: string
results: list<item: struct<axis: string, delta_pp: double, p: double, verdict: string>>
child 0, item: struct<axis: string, delta_pp: double, p: double, verdict: string>
child 0, axis: string
child 1, delta_pp: double
child 2, p: double
child 3, verdict: string
policy: string
human_gate: struct<implementation: string, initial_decision: string, required_for: list<item: string>, competenc (... 55 chars omitted)
child 0, implementation: string
child 1, initial_decision: string
child 2, required_for: list<item: string>
child 0, item: string
child 3, competency_from_live_axis: bool
child 4, approval_may_be_inferred: bool
version: string
rsi_contract: struct<mode: string, asi_claimed: bool, allowed: list<item: string>, forbidden: list<item: string>>
child 0, mode: string
child 1, asi_claimed: bool
child 2, allowed: list<item: string>
child 0, item: string
child 3, forbidden: list<item: string>
child 0, item: string
purpose: string
specialists: list<item: struct<axis: string, mission: string, reviewer_role: string, required_fields: list<item: (... 115 chars omitted)
child 0, item: struct<axis: string, mission: string, reviewer_role: string, required_fields: list<item: string>, au (... 103 chars omitted)
child 0, axis: string
child 1, mission: string
child 2, reviewer_role: string
child 3, required_fields: list<item: string>
child 0, item: string
child 4, audit_focus: list<item: string>
child 0, item: string
child 5, negative_controls: list<item: string>
child 0, item: string
child 6, improvements: list<item: string>
child 0, item: string
cluster_model: struct<isolation: string, state: string, shared_write_access: bool, cross_axis_credentials: bool, no (... 11 chars omitted)
child 0, isolation: string
child 1, state: string
child 2, shared_write_access: bool
child 3, cross_axis_credentials: bool
child 4, note: string
to
{'schema': Value('string'), 'version': Value('string'), 'purpose': Value('string'), 'policy': Value('string'), 'cluster_model': {'isolation': Value('string'), 'state': Value('string'), 'shared_write_access': Value('bool'), 'cross_axis_credentials': Value('bool'), 'note': Value('string')}, 'rsi_contract': {'mode': Value('string'), 'asi_claimed': Value('bool'), 'allowed': List(Value('string')), 'forbidden': List(Value('string'))}, 'human_gate': {'implementation': Value('string'), 'initial_decision': Value('string'), 'required_for': List(Value('string')), 'competency_from_live_axis': Value('bool'), 'approval_may_be_inferred': Value('bool')}, 'specialists': List({'axis': Value('string'), 'mission': Value('string'), 'reviewer_role': Value('string'), 'required_fields': List(Value('string')), 'audit_focus': List(Value('string')), 'negative_controls': List(Value('string')), 'improvements': List(Value('string'))})}
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 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 361, 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 2381, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
schema: string
as_of: timestamp[s]
note: string
results: list<item: struct<axis: string, delta_pp: double, p: double, verdict: string>>
child 0, item: struct<axis: string, delta_pp: double, p: double, verdict: string>
child 0, axis: string
child 1, delta_pp: double
child 2, p: double
child 3, verdict: string
policy: string
human_gate: struct<implementation: string, initial_decision: string, required_for: list<item: string>, competenc (... 55 chars omitted)
child 0, implementation: string
child 1, initial_decision: string
child 2, required_for: list<item: string>
child 0, item: string
child 3, competency_from_live_axis: bool
child 4, approval_may_be_inferred: bool
version: string
rsi_contract: struct<mode: string, asi_claimed: bool, allowed: list<item: string>, forbidden: list<item: string>>
child 0, mode: string
child 1, asi_claimed: bool
child 2, allowed: list<item: string>
child 0, item: string
child 3, forbidden: list<item: string>
child 0, item: string
purpose: string
specialists: list<item: struct<axis: string, mission: string, reviewer_role: string, required_fields: list<item: (... 115 chars omitted)
child 0, item: struct<axis: string, mission: string, reviewer_role: string, required_fields: list<item: string>, au (... 103 chars omitted)
child 0, axis: string
child 1, mission: string
child 2, reviewer_role: string
child 3, required_fields: list<item: string>
child 0, item: string
child 4, audit_focus: list<item: string>
child 0, item: string
child 5, negative_controls: list<item: string>
child 0, item: string
child 6, improvements: list<item: string>
child 0, item: string
cluster_model: struct<isolation: string, state: string, shared_write_access: bool, cross_axis_credentials: bool, no (... 11 chars omitted)
child 0, isolation: string
child 1, state: string
child 2, shared_write_access: bool
child 3, cross_axis_credentials: bool
child 4, note: string
to
{'schema': Value('string'), 'version': Value('string'), 'purpose': Value('string'), 'policy': Value('string'), 'cluster_model': {'isolation': Value('string'), 'state': Value('string'), 'shared_write_access': Value('bool'), 'cross_axis_credentials': Value('bool'), 'note': Value('string')}, 'rsi_contract': {'mode': Value('string'), 'asi_claimed': Value('bool'), 'allowed': List(Value('string')), 'forbidden': List(Value('string'))}, 'human_gate': {'implementation': Value('string'), 'initial_decision': Value('string'), 'required_for': List(Value('string')), 'competency_from_live_axis': Value('bool'), 'approval_may_be_inferred': Value('bool')}, 'specialists': List({'axis': Value('string'), 'mission': Value('string'), 'reviewer_role': Value('string'), 'required_fields': List(Value('string')), 'audit_focus': List(Value('string')), 'negative_controls': List(Value('string')), 'improvements': 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.
GSPC axis specialists
33 agentic specialists — one per GSPC axis — each with a mission, review contract and grading rule
(csoai.axis-specialist-registry/1.0). Specialists are prompt overlays on stock base models
(system prompts, not trained weights; C-2026-0930-11) that route, audit and grade their own axis.
In-lane results (honest, both directions)
| Axis | Specialist delta | p | Verdict |
|---|---|---|---|
| affect | +19.5pp | 0.0078 | significantly better |
| care | +12.6pp | 0.0356 | significantly better |
| governance | +11.4pp | 0.0086 | significantly better |
| cross-reality | −31.2pp | 0.0213 | significantly worse — published as-is |
These are in-lane results (GSPC_PERITEM_AUDIT_20261024 §3). The public board's separations remain TIE/UNTESTED — specialists join no board mean and are never board leaders.
Measurement, not certification. Verify everything: https://councilof.ai/gspc-verify
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