Datasets:
The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: TypeError
Message: Couldn't cast array of type
struct<orders: list<item: string>>
to
{'esi_acuity': Value('int64'), 'urgency_score': Value('int64')}
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, 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 127, 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 483, 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 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, 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 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2312, in cast_table_to_schema
cast_array_to_feature(
~~~~~~~~~~~~~~~~~~~~~^
table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
feature,
^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1861, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2118, in cast_array_to_feature
casted_array_values = _c(array.values, feature.feature)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1863, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2068, in cast_array_to_feature
_c(array.field(name) if name in array_fields else null_array, subfeature)
~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1863, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2158, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
TypeError: Couldn't cast array of type
struct<orders: list<item: string>>
to
{'esi_acuity': Value('int64'), 'urgency_score': Value('int64')}Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
FairMedAgent: instability-floor trajectories
Raw agent trajectories behind the per-action instability floor reported for FairMedAgent, an evaluation harness for demographic disparity in the actions of multi-step clinical LLM agents.
Code, protocol and analysis scripts: https://github.com/rohithreddybc/FairMedAgent
Archived software release: https://doi.org/10.5281/zenodo.22165979 (archival identifier, not the citation)
Why this exists
A counterfactual fairness audit holds the clinical content of a case fixed, changes only the patient descriptor, and reports how often the agent's action changes. On its own that number cannot be interpreted, because an agent's action also changes when nothing changes at all.
These files are the measurement of that baseline. Re-running an identical condition ten times over sixteen vignettes, with the same narrative and the same descriptor string and nothing varied, moved the agent's action in 8.7 percent of outcome-vignette cells. The rate differed across the six actions by a factor of eight, from 0.022 for ICU escalation to 0.179 for controlled-substance caution. A second model gives a pooled floor of 6.7 percent and ranks the six actions almost identically.
No disparity result is claimed here, and none should be quoted from this dataset. The estimand the harness targets counts only flips between actions a published decision rule admits and a clinician has adjudicated as defensible. That adjudication is under way.
Contents
| Path | Contents |
|---|---|
experiments/floor16/ |
Ten repetitions of an identical condition over sixteen vignettes |
experiments/floor16_sonnet/ |
The second-model replication of the same design |
experiments/instability/ |
Earlier instability probe that motivated the floor study |
experiments/pilot, pilot2, pilot3, pilot3ctl |
Pilot runs, including the rare-token, re-render and sham-attribute controls |
docs/DATASHEET.md |
Datasheet for the synthetic cohort |
docs/COHORT_PROVENANCE.md |
Generator version, seed and command, so the cohort is regenerable |
docs/ADJUDICATION_PROTOCOL.md |
How an acceptable-action band is adjudicated |
docs/BAND_ADJUDICATION_RECORD.md |
The adjudicator's reasoning, in full, per band |
Each trajectories.json holds complete six-stage trajectories: five model-facing decisions
around a deterministic environment step, with the condition identifier, the vignette
identifier and the structured action at every stage.
Not included
The development split and the reference leaderboard are published on completion of clinician validation. The held-out test split is sealed and scored under the submission protocol; it is deliberately absent so that it stays a held-out split.
Reproducing the reported numbers
git clone https://github.com/rohithreddybc/FairMedAgent
python FairMedAgent/harness/scripts/verify_paper_numbers.py
The script recomputes all 21 reported quantities from these trajectories. Pass the path to the manuscript source to also assert that each figure appears in the text as computed.
Data statement
All patient vignettes are synthetic. No real patient data, no protected health information, no
human subjects, no IRB required. Cohort provenance is recorded rather than the cohort itself,
so it is regenerable from the seed and command in docs/COHORT_PROVENANCE.md.
Citation
Cite the paper, not the archive. The arXiv preprint is the citable reference and is posted shortly; its identifier is added here as soon as it exists. Zenodo indexes software records but Google Scholar does not, so a Zenodo-only citation does not accrue anywhere a reader or a bibliometric tool will look for it.
10.5281/zenodo.22165979 is the archival identifier for the software itself. It belongs in a data or
code availability statement, which is where journals ask for it, and it is what makes a
specific version of this harness retrievable years from now. It is not the reference to put
in a bibliography.
See CITATION.cff for the machine-readable form.
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