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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_was_wrong', 'gp_flagged', 'answered_by'}) and 14 missing columns ({'missed', 'hedges', 'prompt_tokens', 'completion_tokens', 'unsafe_claims', 'reading_grade', 'model', 'answer', 'refused', 'seconds', 'words', 'call_error', 'bonus_hits', 'cached'}).
This happened while the csv dataset builder was generating data using
hf://datasets/garrec2/lab04-gp-vs-specialist/cascade.csv (at revision a76b1adaba122e036c9fd089b46fdcb03a967d08), ['hf://datasets/garrec2/lab04-gp-vs-specialist@a76b1adaba122e036c9fd089b46fdcb03a967d08/answers.csv', 'hf://datasets/garrec2/lab04-gp-vs-specialist@a76b1adaba122e036c9fd089b46fdcb03a967d08/cascade.csv', 'hf://datasets/garrec2/lab04-gp-vs-specialist@a76b1adaba122e036c9fd089b46fdcb03a967d08/partA_temperature_sweep.csv', 'hf://datasets/garrec2/lab04-gp-vs-specialist@a76b1adaba122e036c9fd089b46fdcb03a967d08/per_question.csv', 'hf://datasets/garrec2/lab04-gp-vs-specialist@a76b1adaba122e036c9fd089b46fdcb03a967d08/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_was_wrong', 'gp_flagged', 'answered_by'}) and 14 missing columns ({'missed', 'hedges', 'prompt_tokens', 'completion_tokens', 'unsafe_claims', 'reading_grade', 'model', 'answer', 'refused', 'seconds', 'words', 'call_error', 'bonus_hits', 'cached'}).
This happened while the csv dataset builder was generating data using
hf://datasets/garrec2/lab04-gp-vs-specialist/cascade.csv (at revision a76b1adaba122e036c9fd089b46fdcb03a967d08), ['hf://datasets/garrec2/lab04-gp-vs-specialist@a76b1adaba122e036c9fd089b46fdcb03a967d08/answers.csv', 'hf://datasets/garrec2/lab04-gp-vs-specialist@a76b1adaba122e036c9fd089b46fdcb03a967d08/cascade.csv', 'hf://datasets/garrec2/lab04-gp-vs-specialist@a76b1adaba122e036c9fd089b46fdcb03a967d08/partA_temperature_sweep.csv', 'hf://datasets/garrec2/lab04-gp-vs-specialist@a76b1adaba122e036c9fd089b46fdcb03a967d08/per_question.csv', 'hf://datasets/garrec2/lab04-gp-vs-specialist@a76b1adaba122e036c9fd089b46fdcb03a967d08/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 | 6.14 | 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 | **Guideline-Directed Medical Therapy (GDMT) for HFrEF (LVEF ≤40%)**
The four core drug classes are:
1. **ACE inhibitors / ARBs / ARNIs** – e.g., lisinopril (current), sacubitril/valsartan (preferred if tolerated)
2. **Beta-blockers** – e.g., carvedilol, metoprolol succinate, bisoprolol
3. **Mineralocorticoid receptor... | 2.39 | 122 | 1,143 | 0 | false | null | 1 | 1 | null | null | null | true | false | 135 | 11.9 |
ddi_warfarin | Drug-drug interaction | liquid/lfm-2.5-2.6b:free | ## Interaction Analysis
### 1. Warfarin + Fluconazole (Current Regimen)
**Mechanism:** Fluconazole is a potent inhibitor of **CYP2C9**, the primary enzyme responsible for metabolizing the active S-enantiomer of warfarin. Inhibition leads to decreased warfarin clearance and elevated plasma concentrations.
**Risk:** W... | 3.93 | 120 | 1,720 | 0 | false | null | 0.75 | 0 | clot | null | cyp2c9|cyp3a4|monitor|ssri | true | false | 322 | 13.9 |
rare_bone | Rare-disease workup | liquid/lfm-2.5-2.6b:free | Based on the clinical | 4.58 | 119 | 2,000 | 0 | false | null | 0 | 0 | osteogenesis imperfecta|col1a1|genetic test | null | null | false | false | 4 | null |
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 SCTID'), google(query='SNOMED CT ICD-10 crosswalk E11.9 type 2 diabetes mellitus')]<|tool_call_end|> | 1.05 | 144 | 194 | 0 | false | null | 0.5 | 0 | granular | null | map | false | false | 30 | 8 |
onc_staging | Oncology staging | nvidia/nemotron-3-ultra-550b-a55b:free | **T category: T2** (tumor >2 cm but ≤5 cm; 2.5 cm invasive carcinoma confined to breast)
**N category: N1** (metastases in 1–3 axillary lymph nodes; 2 positive sentinel nodes)
**M category: M0** (no distant metastases on imaging)
**AJCC Anatomic Stage Group: Stage IIB** (T2 N1 M0)
*Reference: AJCC Cancer Stagin... | 23.84 | 123 | 611 | 0 | false | null | 1 | 1 | null | null | sentinel | false | false | 51 | 13.7 |
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–neprilysin inhibition
2. **Evidence-based β-blocker** — bisoprolol, carvedilol, or metoprolol succinate
3. **MRA** — spironolactone or eplerenone
4. **SGLT2 inhibitor** — dapagliflozin or empagl... | 10.71 | 126 | 1,184 | 0 | false | null | 1 | 1 | null | null | null | false | false | 104 | 12.5 |
ddi_warfarin | Drug-drug interaction | nvidia/nemotron-3-ultra-550b-a55b:free | **Fluconazole–warfarin:**
Fluconazole is a potent **CYP2C9 inhibitor** (the main route of S‑warfarin clearance). It typically **raises INR by 30–100 %** within 3–5 days.
*Guideline/mechanism:* BNF/Stockley’s interaction rating **“severe”**; NICE CG180 recommends **INR check at 3–5 days after starting/stopping** and... | 41.66 | 125 | 670 | 0 | false | null | 1 | 1 | null | null | cyp2c9|cyp3a4 | true | false | 156 | 10.8 |
rare_bone | Rare-disease workup | nvidia/nemotron-3-ultra-550b-a55b:free | **Diagnosis:** Osteogenesis Imperfecta (OI), most consistent with **Type I** (mild, non-deforming) or **Type III/IV** (moderate-severe) given dentinogenesis imperfecta and recurrent fractures. The triad of fractures from minor trauma, blue-grey sclerae, dentinogenesis imperfecta, and **autosomal dominant inheritance ac... | 10.83 | 120 | 627 | 0 | false | null | 1 | 1 | null | null | autosomal dominant | true | false | 135 | 15.5 |
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 (disorder)
**SCTID:** 44054006
ICD-10-CM is a statistical classification optimized for billing and mortality reporting, so a single code (E11.9) lumps together clinically distinct states that SNOMED CT separates into multiple granular concepts (e... | 4.63 | 148 | 410 | 0 | false | null | 1 | 1 | null | null | 44054006 | false | false | 73 | 14.5 |
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 | 0.75 | 0 | null | null | null | null | null | null | null |
rare_bone | Rare-disease workup | null | null | null | null | null | 0 | null | null | 0 | 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 | 16.7 | 60 | null | null | null | null | null | null | null | null | null | null | null | null | null |
null | null | null | null | 22.2 | 60 | null | null | null | null | null | null | null | null | null | null | null | null | null |
null | null | null | null | 28.5 | 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 | 6.14 | 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 | 2.39 | null | 1,143 | 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 | 3.93 | null | 1,720 | 0 | null | null | 0.75 | 0 | null | null | null | null | null | null | null |
rare_bone | Rare-disease workup | liquid/lfm-2.5-2.6b:free | null | 4.58 | null | 2,000 | 0 | null | null | 0 | 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 | 1.05 | null | 194 | 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 | 23.84 | null | 611 | 0 | null | null | 1 | 1 | null | null | null | null | null | null | null |
cardio_gdm | Cardiology guideline | nvidia/nemotron-3-ultra-550b-a55b:free | null | 10.71 | null | 1,184 | 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 | 41.66 | null | 670 | 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 | 10.83 | null | 627 | 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 | 4.63 | null | 410 | 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 | 0.45 | 0.2 | null | null | null | null | null | null | 11.3 |
null | null | nvidia/nemotron-3-ultra-550b-a55b:free | null | null | null | null | null | null | null | 1 | 1 | null | null | null | null | null | null | 13.4 |
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