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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 ({'answered_by', 'gp_flagged', 'escalated', 'gp_was_wrong'}) and 14 missing columns ({'completion_tokens', 'bonus_hits', 'words', 'answer', 'reading_grade', 'prompt_tokens', 'unsafe_claims', 'cached', 'refused', 'call_error', 'missed', 'seconds', 'model', 'hedges'}).
This happened while the csv dataset builder was generating data using
hf://datasets/ruthlesslearner/lab04-gp-vs-specialist/cascade.csv (at revision 20bcfa249e0ae7f9c280d38d23b0763f159f7647), ['hf://datasets/ruthlesslearner/lab04-gp-vs-specialist@20bcfa249e0ae7f9c280d38d23b0763f159f7647/answers.csv', 'hf://datasets/ruthlesslearner/lab04-gp-vs-specialist@20bcfa249e0ae7f9c280d38d23b0763f159f7647/cascade.csv', 'hf://datasets/ruthlesslearner/lab04-gp-vs-specialist@20bcfa249e0ae7f9c280d38d23b0763f159f7647/partA_temperature_sweep.csv', 'hf://datasets/ruthlesslearner/lab04-gp-vs-specialist@20bcfa249e0ae7f9c280d38d23b0763f159f7647/per_question.csv', 'hf://datasets/ruthlesslearner/lab04-gp-vs-specialist@20bcfa249e0ae7f9c280d38d23b0763f159f7647/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 ({'answered_by', 'gp_flagged', 'escalated', 'gp_was_wrong'}) and 14 missing columns ({'completion_tokens', 'bonus_hits', 'words', 'answer', 'reading_grade', 'prompt_tokens', 'unsafe_claims', 'cached', 'refused', 'call_error', 'missed', 'seconds', 'model', 'hedges'}).
This happened while the csv dataset builder was generating data using
hf://datasets/ruthlesslearner/lab04-gp-vs-specialist/cascade.csv (at revision 20bcfa249e0ae7f9c280d38d23b0763f159f7647), ['hf://datasets/ruthlesslearner/lab04-gp-vs-specialist@20bcfa249e0ae7f9c280d38d23b0763f159f7647/answers.csv', 'hf://datasets/ruthlesslearner/lab04-gp-vs-specialist@20bcfa249e0ae7f9c280d38d23b0763f159f7647/cascade.csv', 'hf://datasets/ruthlesslearner/lab04-gp-vs-specialist@20bcfa249e0ae7f9c280d38d23b0763f159f7647/partA_temperature_sweep.csv', 'hf://datasets/ruthlesslearner/lab04-gp-vs-specialist@20bcfa249e0ae7f9c280d38d23b0763f159f7647/per_question.csv', 'hf://datasets/ruthlesslearner/lab04-gp-vs-specialist@20bcfa249e0ae7f9c280d38d23b0763f159f7647/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 | 12.91 | 125 | 2,000 | 0 | false | 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 | Based on the 2022 ACC/AHA/HFSA Guideline for the Management of Heart Failure, the four drug classes that constitute guideline-directed medical therapy (GDMT) for HFrEF are:
1. **Angiotensin system blockers** – ACE inhibitors, ARBs, or ARNIs (angiotensin-converting enzyme inhibitor, angiotensin II receptor blocker, or ... | 5.7 | 122 | 1,231 | 0 | false | null | 1 | 1 | null | null | null | true | false | 171 | 13.1 |
ddi_warfarin | Drug-drug interaction | liquid/lfm-2.5-2.6b:free | ## Interaction Analysis
### St John's Wort and Warfarin
**Mechanism:** St John's wort is a potent inducer of CYP3A4 and P-glycoprotein. Warfarin is metabolized by CYP2C9 (S-warfarin, more potent) and CYP3A4 (R-warfarin). Induction of CYP3A4 increases warfarin clearance, reducing its plasma concentration and thereby l... | 10.92 | 120 | 1,486 | 0 | false | null | 1 | 1 | null | null | cyp2c9|cyp3a4|monitor|ssri|sertraline | true | false | 306 | 11.8 |
rare_bone | Rare-disease workup | liquid/lfm-2.5-2.6b:free | Based on the presentation, the most likely diagnosis is **autosomal recessive osteopetrosis (ROP)**.
**Key features supporting this diagnosis:**
- Multiple fractures from minor trauma (due to dense, poorly resorbed bone)
- Blue-grey sclerae (from anemia secondary to bone marrow infiltration)
- Dentinogenesis imperfect... | 5.85 | 119 | 660 | 0 | false | null | 0.333 | 0 | osteogenesis imperfecta|col1a1 | null | null | true | false | 140 | 38.9 |
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|> | 1.28 | 144 | 186 | 0 | false | 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., Stage Group table) | 27.32 | 123 | 448 | 0 | false | null | 1 | 1 | null | null | null | false | false | 49 | 7 |
cardio_gdm | Cardiology guideline | nvidia/nemotron-3-ultra-550b-a55b:free | **Four GDMT pillars for HFrEF (2022 ACC/AHA/HFSA Guideline):**
1. **ARNI** (preferred) / ACEi / ARB
2. **Evidence-based beta-blocker** (bisoprolol, carvedilol, metoprolol succinate)
3. **MRA** (spironolactone or eplerenone)
4. **SGLT2 inhibitor** (dapagliflozin or empagliflozin)
**First change:** Switch lisinopr... | 20.28 | 126 | 1,038 | 0 | false | null | 1 | 1 | null | null | titrate | true | false | 98 | 11.8 |
ddi_warfarin | Drug-drug interaction | nvidia/nemotron-3-ultra-550b-a55b:free | **Fluconazole–warfarin**
- **Mechanism:** Fluconazole is a potent **CYP2C9 inhibitor** (primary metabolic pathway for S‑warfarin) and also inhibits CYP3A4.
- **Effect:** ↑ warfarin exposure → **INR rise**, bleeding risk. Well‑documented, often requiring 20–50% warfarin dose reduction.
- **Guideline/Reference:** C... | 85.76 | 125 | 776 | 0 | false | null | 1 | 1 | null | null | cyp2c9|cyp3a4|monitor|ssri|sertraline | true | false | 194 | 11 |
rare_bone | Rare-disease workup | nvidia/nemotron-3-ultra-550b-a55b:free | **Diagnosis:** Osteogenesis imperfecta (OI), most consistent with **autosomal dominant OI type I/III/IV** (Sillence classification) given blue‑grey sclerae, dentinogenesis imperfecta, recurrent low‑trauma fractures, and a three‑generation pedigree.
**Genes most often involved:**
- **COL1A1** (OMIM 120150) – ~90 % of... | 23.61 | 120 | 633 | 0 | false | null | 1 | 1 | null | null | autosomal dominant | true | false | 110 | 18.6 |
onto_map | Ontology mapping (ICD-10-CM to SNOMED CT) | nvidia/nemotron-3-ultra-550b-a55b:free | **SNOMED CT concept:** Type 2 diabetes mellitus without complication
**SCTID:** 44054006
ICD-10-CM codes are designed for statistical classification and billing, so a single code often lumps together clinically distinct states that SNOMED CT separates into multiple finer-grained concepts. Conversely, SNOMED CT’s c... | 4.94 | 148 | 290 | 0 | false | null | 1 | 1 | null | null | 44054006|map | false | false | 76 | 16.2 |
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 | 18.4 | 60 | null | null | null | null | null | null | null | null | null | null | null | null | null |
null | null | null | null | 27.3 | 60 | null | null | null | null | null | null | null | null | null | null | null | null | null |
null | null | null | null | 22.6 | 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 | 12.91 | 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 | 5.7 | null | 1,231 | 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 | 10.92 | null | 1,486 | 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 | 5.85 | null | 660 | 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 | 1.28 | 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 | 27.32 | null | 448 | 0 | null | null | 1 | 1 | null | null | null | null | null | null | null |
cardio_gdm | Cardiology guideline | nvidia/nemotron-3-ultra-550b-a55b:free | null | 20.28 | null | 1,038 | 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 | 85.76 | null | 776 | 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 | 23.61 | null | 633 | 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 | 4.94 | null | 290 | 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 | 17.5 |
null | null | nvidia/nemotron-3-ultra-550b-a55b:free | null | null | null | null | null | null | null | 1 | 1 | null | null | null | null | null | null | 12.9 |
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