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The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 4 new columns ({'escalated', 'gp_flagged', 'gp_was_wrong', 'answered_by'}) and 14 missing columns ({'answer', 'refused', 'bonus_hits', 'model', 'words', 'missed', 'hedges', 'completion_tokens', 'unsafe_claims', 'reading_grade', 'cached', 'seconds', 'call_error', 'prompt_tokens'}).
This happened while the csv dataset builder was generating data using
hf://datasets/coinhead/lab04-gp-vs-specialist/cascade.csv (at revision 1936e6482817aa8d3e87132122bccdbcd28ce5ef), ['hf://datasets/coinhead/lab04-gp-vs-specialist@1936e6482817aa8d3e87132122bccdbcd28ce5ef/answers.csv', 'hf://datasets/coinhead/lab04-gp-vs-specialist@1936e6482817aa8d3e87132122bccdbcd28ce5ef/cascade.csv', 'hf://datasets/coinhead/lab04-gp-vs-specialist@1936e6482817aa8d3e87132122bccdbcd28ce5ef/partA_temperature_sweep.csv', 'hf://datasets/coinhead/lab04-gp-vs-specialist@1936e6482817aa8d3e87132122bccdbcd28ce5ef/per_question.csv', 'hf://datasets/coinhead/lab04-gp-vs-specialist@1936e6482817aa8d3e87132122bccdbcd28ce5ef/scorecard.csv']
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1848, in _prepare_split_single
writer.write_table(table)
~~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
self._write_table(pa_table, writer_batch_size=writer_batch_size)
~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
pa_table = table_cast(pa_table, self._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 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
question: string
domain: string
escalated: bool
answered_by: string
coverage: double
full_credit: int64
cost_usd: double
gp_flagged: bool
gp_was_wrong: bool
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1327
to
{'question': Value('string'), 'domain': Value('string'), 'model': Value('string'), 'answer': Value('string'), 'seconds': Value('float64'), 'prompt_tokens': Value('int64'), 'completion_tokens': Value('int64'), 'cost_usd': Value('float64'), 'cached': Value('bool'), 'call_error': Value('string'), 'coverage': Value('float64'), 'full_credit': Value('int64'), 'missed': Value('string'), 'unsafe_claims': Value('float64'), 'bonus_hits': Value('string'), 'hedges': Value('bool'), 'refused': Value('bool'), 'words': Value('int64'), 'reading_grade': Value('float64')}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1850, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
...<4 lines>...
)
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 4 new columns ({'escalated', 'gp_flagged', 'gp_was_wrong', 'answered_by'}) and 14 missing columns ({'answer', 'refused', 'bonus_hits', 'model', 'words', 'missed', 'hedges', 'completion_tokens', 'unsafe_claims', 'reading_grade', 'cached', 'seconds', 'call_error', 'prompt_tokens'}).
This happened while the csv dataset builder was generating data using
hf://datasets/coinhead/lab04-gp-vs-specialist/cascade.csv (at revision 1936e6482817aa8d3e87132122bccdbcd28ce5ef), ['hf://datasets/coinhead/lab04-gp-vs-specialist@1936e6482817aa8d3e87132122bccdbcd28ce5ef/answers.csv', 'hf://datasets/coinhead/lab04-gp-vs-specialist@1936e6482817aa8d3e87132122bccdbcd28ce5ef/cascade.csv', 'hf://datasets/coinhead/lab04-gp-vs-specialist@1936e6482817aa8d3e87132122bccdbcd28ce5ef/partA_temperature_sweep.csv', 'hf://datasets/coinhead/lab04-gp-vs-specialist@1936e6482817aa8d3e87132122bccdbcd28ce5ef/per_question.csv', 'hf://datasets/coinhead/lab04-gp-vs-specialist@1936e6482817aa8d3e87132122bccdbcd28ce5ef/scorecard.csv']
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)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.
question string | domain string | model string | answer string | seconds float64 | prompt_tokens int64 | completion_tokens int64 | cost_usd float64 | cached bool | call_error string | coverage float64 | full_credit int64 | missed string | unsafe_claims null | bonus_hits string | hedges bool | refused bool | words int64 | reading_grade float64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
onc_staging | Oncology staging | liquid/lfm-2.5-2.6b:free | null | 9.95 | 125 | 2,000 | 0 | true | empty answer: all 2000 completion tokens went to reasoning (2000). Raise MAX_TOKENS. | 0 | 0 | t2|n1|m0|iib | null | null | false | false | 0 | null |
cardio_gdm | Cardiology guideline | liquid/lfm-2.5-2.6b:free | **Four drug classes in guideline-directed medical therapy for HFrEF:**
1. **ACE inhibitors / ARBs / ARNIs** – e.g., lisinopril (already on), sacubitril/valsartan
2. **Beta-blockers** – e.g., carvedilol, bisoprolol, metoprolol succinate
3. **Mineralocorticoid receptor antagonists (MRAs)** – e.g., spironolactone, eplere... | 7.31 | 122 | 1,060 | 0 | true | null | 1 | 1 | null | null | null | true | false | 118 | 12 |
ddi_warfarin | Drug-drug interaction | liquid/lfm-2.5-2.6b:free | **Interaction Explanation**
**Warfarin + St John's wort = significant reduction in warfarin plasma concentration.**
Mechanism: St John's wort is a potent inducer of **CYP3A4** and **P-glycoprotein**. Warfarin is primarily metabolized by CYP2C9 (S-warfarin) and CYP3A4 (R-warfarin). Induction of these pathways accelera... | 9.48 | 120 | 835 | 0 | true | null | 1 | 1 | null | null | cyp2c9|cyp3a4|monitor|sertraline | true | false | 297 | 12.9 |
rare_bone | Rare-disease workup | liquid/lfm-2.5-2.6b:free | Based on the clinical presentation, the most likely diagnosis is **autosomal dominant osteopetrosis**.
**Genes most often involved:**
- **RAB7** — responsible for approximately 70% of cases; accounts for the majority of autosomal dominant osteopetrosis
- **LRRC1** — associated with autosomal recessive osteopetrosis (l... | 6.12 | 119 | 923 | 0 | true | null | 0.333 | 0 | osteogenesis imperfecta|col1a1 | null | autosomal dominant|bisphosphonate | true | false | 140 | 22 |
onto_map | Ontology mapping (ICD-10-CM to SNOMED CT) | liquid/lfm-2.5-2.6b:free | <|tool_call_start|>[google(query='ICD-10-CM E11.9 Type 2 diabetes mellitus without complications SNOMED CT mapping'), google(query='SNOMED CT ICD-10 crosswalk E11.9')]<|tool_call_end|> | 1.13 | 144 | 186 | 0 | true | null | 0.5 | 0 | granular | null | map | false | false | 27 | 6.3 |
onc_staging | Oncology staging | nvidia/nemotron-3-ultra-550b-a55b:free | **T category: T2** (tumor >2 cm but ≤5 cm; AJCC 8th ed., breast cancer staging)
**N category: N1** (metastases in 1–3 axillary lymph nodes; AJCC 8th ed.)
**M category: M0** (no distant metastases on imaging; AJCC 8th ed.)
**Anatomic stage group: Stage IIB** (T2 N1 M0; AJCC 8th ed., anatomic stage groups for brea... | 9.89 | 123 | 540 | 0 | true | null | 1 | 1 | null | null | null | false | false | 52 | 7.5 |
cardio_gdm | Cardiology guideline | nvidia/nemotron-3-ultra-550b-a55b:free | **Four GDMT pillars for HFrEF (ACC/AHA/HFSA 2022; ESC 2021):**
1. **ARNI (preferred) / ACEi / ARB** — renin–angiotensin inhibition
2. **Beta-blocker** (bisoprolol, carvedilol, or sustained-release metoprolol succinate)
3. **MRA** (spironolactone or eplerenone)
4. **SGLT2 inhibitor** (dapagliflozin or empagliflozi... | 14.74 | 126 | 796 | 0 | true | null | 1 | 1 | null | null | null | false | false | 91 | 13 |
ddi_warfarin | Drug-drug interaction | nvidia/nemotron-3-ultra-550b-a55b:free | **1. Fluconazole + warfarin**
- **Mechanism:** Fluconazole is a potent inhibitor of **CYP2C9** (primary metabolic pathway for S‑warfarin) and a moderate inhibitor of CYP3A4.
- **Effect:** Increases warfarin exposure → **INR rises**, often markedly, within 3–7 days. Bleeding risk increases.
- **Evidence:** FDA war... | 12.47 | 125 | 855 | 0 | true | null | 1 | 1 | null | null | cyp2c9|cyp3a4|monitor | true | false | 238 | 11.9 |
rare_bone | Rare-disease workup | nvidia/nemotron-3-ultra-550b-a55b:free | **Diagnosis:** Osteogenesis Imperfecta (OI), most likely Type I or III/IV (autosomal dominant).
**Genes most often involved:** *COL1A1* and *COL1A2* (together account for >90% of clinically diagnosed OI).
**Confirmatory test:** Molecular genetic testing — next-generation sequencing (NGS) panel or targeted sequenc... | 10 | 120 | 398 | 0 | true | null | 1 | 1 | null | null | autosomal dominant | true | false | 73 | 16.4 |
onto_map | Ontology mapping (ICD-10-CM to SNOMED CT) | nvidia/nemotron-3-ultra-550b-a55b:free | **Mapping**
The standard ICD-10-CM→SNOMED CT map (NLM/CMS) points E11.9 to **44054006 | Type 2 diabetes mellitus (disorder) |**.
*Note:* The U.S. Edition of SNOMED CT also contains a more specific concept **422615004 | Type 2 diabetes mellitus without complication (disorder) |**, which may be a better clinical fit ... | 75.99 | 148 | 1,675 | 0 | true | null | 1 | 1 | null | null | 44054006|map | false | false | 125 | 13.9 |
onc_staging | Oncology staging | null | null | null | null | null | 0 | null | null | 0 | 0 | null | null | null | null | null | null | null |
cardio_gdm | Cardiology guideline | null | null | null | null | null | 0 | null | null | 1 | 1 | null | null | null | null | null | null | null |
ddi_warfarin | Drug-drug interaction | null | null | null | null | null | 0 | null | null | 1 | 1 | null | null | null | null | null | null | null |
rare_bone | Rare-disease workup | null | null | null | null | null | 0 | null | null | 0.333 | 0 | null | null | null | null | null | null | null |
onto_map | Ontology mapping (ICD-10-CM to SNOMED CT) | null | null | null | null | null | 0 | null | null | 0.5 | 0 | null | null | null | null | null | null | null |
null | null | null | null | 4.4 | 60 | null | null | null | null | null | null | null | null | null | null | null | null | null |
null | null | null | null | 10 | 60 | null | null | null | null | null | null | null | null | null | null | null | null | null |
null | null | null | null | 7.8 | 60 | null | null | null | null | null | null | null | null | null | null | null | null | null |
onc_staging | Oncology staging | liquid/lfm-2.5-2.6b:free | null | 9.95 | null | 2,000 | 0 | null | null | 0 | 0 | null | null | null | null | null | null | null |
cardio_gdm | Cardiology guideline | liquid/lfm-2.5-2.6b:free | null | 7.31 | null | 1,060 | 0 | null | null | 1 | 1 | null | null | null | null | null | null | null |
ddi_warfarin | Drug-drug interaction | liquid/lfm-2.5-2.6b:free | null | 9.48 | null | 835 | 0 | null | null | 1 | 1 | null | null | null | null | null | null | null |
rare_bone | Rare-disease workup | liquid/lfm-2.5-2.6b:free | null | 6.12 | null | 923 | 0 | null | null | 0.333 | 0 | null | null | null | null | null | null | null |
onto_map | Ontology mapping (ICD-10-CM to SNOMED CT) | liquid/lfm-2.5-2.6b:free | null | 1.13 | null | 186 | 0 | null | null | 0.5 | 0 | null | null | null | null | null | null | null |
onc_staging | Oncology staging | nvidia/nemotron-3-ultra-550b-a55b:free | null | 9.89 | null | 540 | 0 | null | null | 1 | 1 | null | null | null | null | null | null | null |
cardio_gdm | Cardiology guideline | nvidia/nemotron-3-ultra-550b-a55b:free | null | 14.74 | null | 796 | 0 | null | null | 1 | 1 | null | null | null | null | null | null | null |
ddi_warfarin | Drug-drug interaction | nvidia/nemotron-3-ultra-550b-a55b:free | null | 12.47 | null | 855 | 0 | null | null | 1 | 1 | null | null | null | null | null | null | null |
rare_bone | Rare-disease workup | nvidia/nemotron-3-ultra-550b-a55b:free | null | 10 | null | 398 | 0 | null | null | 1 | 1 | null | null | null | null | null | null | null |
onto_map | Ontology mapping (ICD-10-CM to SNOMED CT) | nvidia/nemotron-3-ultra-550b-a55b:free | null | 75.99 | null | 1,675 | 0 | null | null | 1 | 1 | null | null | null | null | null | null | null |
null | null | liquid/lfm-2.5-2.6b:free | null | null | null | null | null | null | null | 0.567 | 0.4 | null | null | null | null | null | null | 13.3 |
null | null | nvidia/nemotron-3-ultra-550b-a55b:free | null | null | null | null | null | null | null | 1 | 1 | null | null | null | null | null | null | 12.5 |
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