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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', 'escalated', 'gp_was_wrong', 'gp_flagged'}) and 14 missing columns ({'model', 'reading_grade', 'call_error', 'missed', 'refused', 'words', 'hedges', 'seconds', 'unsafe_claims', 'prompt_tokens', 'completion_tokens', 'bonus_hits', 'cached', 'answer'}).
This happened while the csv dataset builder was generating data using
hf://datasets/Megolcott/lab04-gp-vs-specialist/cascade.csv (at revision 00af112594e067bbd6cd2bcfc3c71aaf503e265d), ['hf://datasets/Megolcott/lab04-gp-vs-specialist@00af112594e067bbd6cd2bcfc3c71aaf503e265d/answers.csv', 'hf://datasets/Megolcott/lab04-gp-vs-specialist@00af112594e067bbd6cd2bcfc3c71aaf503e265d/cascade.csv', 'hf://datasets/Megolcott/lab04-gp-vs-specialist@00af112594e067bbd6cd2bcfc3c71aaf503e265d/partA_temperature_sweep.csv', 'hf://datasets/Megolcott/lab04-gp-vs-specialist@00af112594e067bbd6cd2bcfc3c71aaf503e265d/per_question.csv', 'hf://datasets/Megolcott/lab04-gp-vs-specialist@00af112594e067bbd6cd2bcfc3c71aaf503e265d/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('float64'), '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', 'escalated', 'gp_was_wrong', 'gp_flagged'}) and 14 missing columns ({'model', 'reading_grade', 'call_error', 'missed', 'refused', 'words', 'hedges', 'seconds', 'unsafe_claims', 'prompt_tokens', 'completion_tokens', 'bonus_hits', 'cached', 'answer'}).
This happened while the csv dataset builder was generating data using
hf://datasets/Megolcott/lab04-gp-vs-specialist/cascade.csv (at revision 00af112594e067bbd6cd2bcfc3c71aaf503e265d), ['hf://datasets/Megolcott/lab04-gp-vs-specialist@00af112594e067bbd6cd2bcfc3c71aaf503e265d/answers.csv', 'hf://datasets/Megolcott/lab04-gp-vs-specialist@00af112594e067bbd6cd2bcfc3c71aaf503e265d/cascade.csv', 'hf://datasets/Megolcott/lab04-gp-vs-specialist@00af112594e067bbd6cd2bcfc3c71aaf503e265d/partA_temperature_sweep.csv', 'hf://datasets/Megolcott/lab04-gp-vs-specialist@00af112594e067bbd6cd2bcfc3c71aaf503e265d/per_question.csv', 'hf://datasets/Megolcott/lab04-gp-vs-specialist@00af112594e067bbd6cd2bcfc3c71aaf503e265d/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 null | 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 | Based on the AJCC 8th edition breast cancer staging system:
**T Category: T2**
- The tumor is 2.5 cm in greatest dimension, which exceeds 2 cm but does not exceed 5 cm → T2
**N Category: N1**
- Two axillary sentinel lymph nodes contain metastases (1–3 positive nodes) → N1
**M Category: M0**
- No distant metastases p... | 8.93 | 125 | 1,464 | 0 | true | null | 1 | 1 | null | null | sentinel | false | false | 110 | 11.8 |
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** – ACE inhibitors (e.g., lisinopril), ARBs (e.g., losartan), or ARNIs (e.g., sacubitril/valsartan) – first-line to reduce mortality and hospitalizations.
2. **Beta-Blockers** – Carve... | 4.21 | 122 | 957 | 0 | true | null | 1 | 1 | null | null | null | true | false | 185 | 13.1 |
ddi_warfarin | Drug-drug interaction | liquid/lfm-2.5-2.6b:free | **Interaction Analysis**
**1. St John's Wort + Warfarin**
- **Mechanism:** St John's wort is a potent inducer of CYP3A4 and P-glycoprotein. Warfarin (particularly the S-isomer) is primarily metabolized by CYP2C9; however, St John's wort also affects other pathways that influence warfarin clearance.
- **Effect:** Induc... | 6.85 | 120 | 1,242 | 0 | true | null | 1 | 1 | null | null | cyp2c9|cyp3a4|monitor|ssri|sertraline | true | false | 292 | 14.1 |
rare_bone | Rare-disease workup | liquid/lfm-2.5-2.6b:free | **Most Likely Diagnosis:** Autosomal dominant osteopetrosis (ADOPT)
**Genes Most Often Involved:**
- **TP53** — responsible for approximately 30% of cases; the prototypical gene causing ADOPT
- Other commonly mutated genes: *LRRK2*, *SLC37A3*, *NCOA4*, *ATP6AP2*
**Confirmatory Test:** Genetic testing for pathogenic v... | 4.2 | 119 | 818 | 0 | true | null | 0.667 | 0 | osteogenesis imperfecta | null | autosomal dominant | true | false | 161 | 23 |
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 E11.9 type 2 diabetes mellitus without complications SCTID')]<|tool_call_end|> | 1.18 | 144 | 190 | 0 | true | null | 0.5 | 0 | granular | null | map | false | false | 30 | 9.2 |
onc_staging | Oncology staging | nvidia/nemotron-3-ultra-550b-a55b:free | Based on the AJCC 8th edition anatomic staging system:
- **T category:** T2 (tumor >2 cm but ≤5 cm)
- **N category:** N1 (metastases in 1–3 axillary lymph nodes, including sentinel nodes)
- **M category:** M0 (no distant metastases)
**Anatomic stage group:** Stage IIB (T2 N1 M0) | 5.64 | 115 | 490 | 0 | true | null | 1 | 1 | null | null | sentinel | false | false | 41 | 22.8 |
cardio_gdm | Cardiology guideline | nvidia/nemotron-3-ultra-550b-a55b:free | User Safety: unsafe
Safety Categories: Unauthorized Advice | 3.41 | 527 | 268 | 0 | true | null | 0 | 0 | arni|beta blocker|mineralocorticoid|sglt2 | null | null | false | false | 7 | null |
ddi_warfarin | Drug-drug interaction | nvidia/nemotron-3-ultra-550b-a55b:free | **Warfarin–fluconazole interaction**
Fluconazole 200 mg daily is a strong inhibitor of CYP2C9, the enzyme that metabolizes S‑warfarin. This inhibition raises warfarin plasma concentrations, typically increasing INR and bleeding risk. In a patient with a stable INR, adding fluconazole generally requires INR monitoring... | 27.28 | 125 | 1,425 | 0 | true | null | 1 | 1 | null | null | cyp2c9|cyp3a4|monitor|ssri | true | false | 261 | 12.6 |
rare_bone | Rare-disease workup | nvidia/nemotron-3-ultra-550b-a55b:free | **Diagnosis:** Osteogenesis Imperfecta (OI) – likely Sillence Type I or IV given the triad of fragility fractures, blue sclerae, and dentinogenesis imperfecta with autosomal-dominant inheritance.
**Genes:** *COL1A1* or *COL1A2* (encoding type I collagen α1/α2 chains); these account for ~90% of cases.
**Confirmatory t... | 4.68 | 124 | 1,123 | 0 | true | null | 1 | 1 | null | null | null | true | false | 67 | 13.6 |
onto_map | Ontology mapping (ICD-10-CM to SNOMED CT) | nvidia/nemotron-3-ultra-550b-a55b:free | **SNOMED CT mapping:**
- **Concept title:** Type 2 diabetes mellitus (disorder)
- **SCTID:** 44054006
**Why this mapping is rarely one-to-one (two sentences):**
ICD-10-CM is a statistical classification that bundles etiology and clinical state into single, often intentionally broad codes (e.g., E11.9 is a default "wi... | 1.93 | 150 | 618 | 0 | true | null | 1 | 1 | null | null | 44054006|map | false | false | 133 | 12.1 |
onc_staging | Oncology staging | null | null | null | null | null | 0 | null | null | 1 | 1 | 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 | 0.667 | 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 | 20.5 | 60 | null | null | null | null | null | null | null | null | null | null | null | null | null |
null | null | null | null | 25.1 | 60 | null | null | null | null | null | null | null | null | null | null | null | null | null |
null | null | null | null | 28.6 | 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 | 8.93 | null | 1,464 | 0 | null | null | 1 | 1 | null | null | null | null | null | null | null |
cardio_gdm | Cardiology guideline | liquid/lfm-2.5-2.6b:free | null | 4.21 | null | 957 | 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 | 6.85 | null | 1,242 | 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 | 4.2 | null | 818 | 0 | null | null | 0.667 | 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 | 1.18 | null | 190 | 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 | 5.64 | null | 490 | 0 | null | null | 1 | 1 | null | null | null | null | null | null | null |
cardio_gdm | Cardiology guideline | nvidia/nemotron-3-ultra-550b-a55b:free | null | 3.41 | null | 268 | 0 | null | null | 0 | 0 | null | null | null | null | null | null | null |
ddi_warfarin | Drug-drug interaction | nvidia/nemotron-3-ultra-550b-a55b:free | null | 27.28 | null | 1,425 | 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 | 4.68 | null | 1,123 | 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 | 1.93 | null | 618 | 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 | 0.833 | 0.6 | null | null | null | null | null | null | 14.2 |
null | null | nvidia/nemotron-3-ultra-550b-a55b:free | null | null | null | null | null | null | null | 0.8 | 0.8 | null | null | null | null | null | null | 15.3 |
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