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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 6 new columns ({'prompt', 'gold', 'type', 'id', 'acceptable', 'tests'}) and 19 missing columns ({'domain', 'seconds', 'question', 'completion_tokens', 'reading_grade', 'bonus_hits', 'words', 'model', 'full_credit', 'unsafe_claims', 'answer', 'cost_usd', 'cached', 'coverage', 'missed', 'call_error', 'prompt_tokens', 'refused', 'hedges'}).
This happened while the csv dataset builder was generating data using
hf://datasets/winnetka/lab07-catch-the-ai-lying/gold_qa.csv (at revision adc14e5d533107b25a96712d3e4f4dcb06b2d40f), ['hf://datasets/winnetka/lab07-catch-the-ai-lying@adc14e5d533107b25a96712d3e4f4dcb06b2d40f/answers.csv', 'hf://datasets/winnetka/lab07-catch-the-ai-lying@adc14e5d533107b25a96712d3e4f4dcb06b2d40f/gold_qa.csv', 'hf://datasets/winnetka/lab07-catch-the-ai-lying@adc14e5d533107b25a96712d3e4f4dcb06b2d40f/lab07_agreement.csv', 'hf://datasets/winnetka/lab07-catch-the-ai-lying@adc14e5d533107b25a96712d3e4f4dcb06b2d40f/lab07_answers.csv', 'hf://datasets/winnetka/lab07-catch-the-ai-lying@adc14e5d533107b25a96712d3e4f4dcb06b2d40f/lab07_confusion.csv', 'hf://datasets/winnetka/lab07-catch-the-ai-lying@adc14e5d533107b25a96712d3e4f4dcb06b2d40f/lab07_judge_runs.csv', 'hf://datasets/winnetka/lab07-catch-the-ai-lying@adc14e5d533107b25a96712d3e4f4dcb06b2d40f/lab07_verdicts.csv', 'hf://datasets/winnetka/lab07-catch-the-ai-lying@adc14e5d533107b25a96712d3e4f4dcb06b2d40f/lab4_rescored.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 784, 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 795, 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
id: string
type: string
prompt: string
gold: string
acceptable: string
tests: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 940
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 6 new columns ({'prompt', 'gold', 'type', 'id', 'acceptable', 'tests'}) and 19 missing columns ({'domain', 'seconds', 'question', 'completion_tokens', 'reading_grade', 'bonus_hits', 'words', 'model', 'full_credit', 'unsafe_claims', 'answer', 'cost_usd', 'cached', 'coverage', 'missed', 'call_error', 'prompt_tokens', 'refused', 'hedges'}).
This happened while the csv dataset builder was generating data using
hf://datasets/winnetka/lab07-catch-the-ai-lying/gold_qa.csv (at revision adc14e5d533107b25a96712d3e4f4dcb06b2d40f), ['hf://datasets/winnetka/lab07-catch-the-ai-lying@adc14e5d533107b25a96712d3e4f4dcb06b2d40f/answers.csv', 'hf://datasets/winnetka/lab07-catch-the-ai-lying@adc14e5d533107b25a96712d3e4f4dcb06b2d40f/gold_qa.csv', 'hf://datasets/winnetka/lab07-catch-the-ai-lying@adc14e5d533107b25a96712d3e4f4dcb06b2d40f/lab07_agreement.csv', 'hf://datasets/winnetka/lab07-catch-the-ai-lying@adc14e5d533107b25a96712d3e4f4dcb06b2d40f/lab07_answers.csv', 'hf://datasets/winnetka/lab07-catch-the-ai-lying@adc14e5d533107b25a96712d3e4f4dcb06b2d40f/lab07_confusion.csv', 'hf://datasets/winnetka/lab07-catch-the-ai-lying@adc14e5d533107b25a96712d3e4f4dcb06b2d40f/lab07_judge_runs.csv', 'hf://datasets/winnetka/lab07-catch-the-ai-lying@adc14e5d533107b25a96712d3e4f4dcb06b2d40f/lab07_verdicts.csv', 'hf://datasets/winnetka/lab07-catch-the-ai-lying@adc14e5d533107b25a96712d3e4f4dcb06b2d40f/lab4_rescored.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 diameter, which exceeds 2 cm but does not exceed 5 cm. Per AJCC 8th Edition, tumors >2 cm but ≤5 cm confined to the breast are classified as **T2**.
**N Category: N1**
- There are two axillary sentinel lymph nodes ... | 56.57 | 125 | 1,448 | 0 | false | null | 1 | 1 | null | null | sentinel | false | false | 130 | 9.7 |
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., sacubitril/valsartan (ARNI), enalapril, losartan
2. **Beta-blockers** – e.g., carvedilol, metoprolol succinate, bisoprolol
3. **Mineralocorticoid receptor antagonists (MRAs)** – e.g., spironolactone, epl... | 35.3 | 122 | 877 | 0 | false | null | 1 | 1 | null | null | null | true | false | 112 | 11.9 |
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 is primarily metabolized by CYP2C9 (for S-warfarin) and CYP3A4 (for R-warfarin). Induction of CYP3A4 accelerates R-warfarin clearance, reducing its plasma concentration and... | 63.2 | 120 | 1,487 | 0 | false | null | 1 | 1 | null | null | cyp2c9|cyp3a4|monitor|ssri|sertraline | false | false | 299 | 12.9 |
rare_bone | Rare-disease workup | liquid/lfm-2.5-2.6b:free | **Most Likely Diagnosis:** Osteogenesis Imperfecta (OI), also called brittle bone disease.
**Genes Most Often Involved:**
- **COL1A1** and **COL1A2** — responsible for approximately 70–80% of OI cases (autosomal dominant form, Type I).
- Other genes (CRTAP, P3H1, WNT1, SERPINF1, BMPR1A) account for rarer subtypes.
**... | 62.75 | 119 | 1,135 | 0 | false | null | 1 | 1 | null | null | autosomal dominant | true | false | 116 | 13.9 |
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 SCTID'), google(query='SNOMED CT ICD-10 crosswalk E11.9 type 2 diabetes mellitus without complications')]<|tool_call_end|> | 14.05 | 144 | 196 | 0 | false | null | 0.5 | 0 | granular | null | map | false | false | 32 | 9.2 |
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; two positive sentinel nodes)
**M category: M0** (no distant metastases on imaging)
**AJCC Anatomic Stage Group: Stage IIB** (T2 N1 M0)
*Reference: AJCC Cancer Stag... | 8.39 | 123 | 580 | 0 | false | null | 1 | 1 | null | null | sentinel | false | false | 52 | 13.6 |
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
2. **Evidence-based β-blocker** (carvedilol, metoprolol succinate, bisoprolol)
3. **MRA** (spironolactone or eplerenone)
4. **SGLT2 inhibitor** (dapagliflozin or empagliflozin)
**First change for this patient:** ... | 15.41 | 126 | 787 | 0 | false | null | 1 | 1 | null | null | null | false | false | 77 | 14 |
ddi_warfarin | Drug-drug interaction | nvidia/nemotron-3-ultra-550b-a55b:free | **Fluconazole–warfarin**
- **Mechanism:** Fluconazole is a potent **CYP2C9 inhibitor** (also inhibits CYP3A4). S‑warfarin (the more active enantiomer) is primarily metabolised by CYP2C9. Inhibition → ↑ warfarin levels → ↑ INR → bleeding risk.
- **Evidence:** Well‑documented; listed in warfarin FDA labelling, Stockl... | 17.72 | 125 | 993 | 0 | false | null | 1 | 1 | null | null | cyp2c9|cyp3a4|monitor|sertraline | true | false | 188 | 11.2 |
rare_bone | Rare-disease workup | nvidia/nemotron-3-ultra-550b-a55b:free | **Diagnosis:** Osteogenesis imperfecta (OI), most consistent with **Type I** (mild, autosomal dominant) given survival to age 9 with blue-grey sclerae, dentinogenesis imperfecta, and multi-generational family history.
**Genes most often involved:**
- **COL1A1** (≈90% of pathogenic variants)
- **COL1A2** (≈10%) ... | 10.63 | 120 | 586 | 0 | false | null | 1 | 1 | null | null | autosomal dominant | true | false | 108 | 18.9 |
onto_map | Ontology mapping (ICD-10-CM to SNOMED CT) | nvidia/nemotron-3-ultra-550b-a55b:free | **SNOMED CT concept:** Type 2 diabetes mellitus (disorder)
**SCTID:** 44054006
**Mapping note:** The NLM ICD-10-CM to SNOMED CT map assigns a “source-is-narrower-than-target” relationship because ICD-10-CM E11.9 explicitly states “without complications,” while the SNOMED CT concept 44054006 represents the disorder... | 12.27 | 148 | 879 | 0 | false | null | 1 | 1 | null | null | 44054006|map | false | false | 127 | 21 |
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null | null | liquid/lfm-2.5-2.6b:free | E11.9 | 1.41 | 121 | 175 | 0 | true | null | null | null | null | null | null | null | null | null | null |
null | null | liquid/lfm-2.5-2.6b:free | I20.0 | 1.09 | 110 | 216 | 0 | true | null | null | null | null | null | null | null | null | null | null |
null | null | liquid/lfm-2.5-2.6b:free | 290410006 | 0.71 | 102 | 166 | 0 | true | null | null | null | null | null | null | null | null | null | null |
null | null | liquid/lfm-2.5-2.6b:free | 6 | 2.64 | 107 | 536 | 0 | true | null | null | null | null | null | null | null | null | null | null |
null | null | liquid/lfm-2.5-2.6b:free | 183 | 0.75 | 132 | 184 | 0 | true | null | null | null | null | null | null | null | null | null | null |
null | null | liquid/lfm-2.5-2.6b:free | 70 | 1.69 | 105 | 192 | 0 | true | null | null | null | null | null | null | null | null | null | null |
null | null | liquid/lfm-2.5-2.6b:free | 18 | 1.64 | 106 | 451 | 0 | true | null | null | null | null | null | null | null | null | null | null |
null | null | liquid/lfm-2.5-2.6b:free | prothrombin complex concentrate (PCC) | 1.38 | 115 | 440 | 0 | true | null | null | null | null | null | null | null | null | null | null |
null | null | liquid/lfm-2.5-2.6b:free | NO | 1.06 | 114 | 191 | 0 | true | null | null | null | null | null | null | null | null | null | null |
null | null | liquid/lfm-2.5-2.6b:free | high | 1.04 | 100 | 228 | 0 | true | null | null | null | null | null | null | null | null | null | null |
null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
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null | null | liquid/lfm-2.5-2.6b:free | E11.9 | 1.41 | 121 | 175 | 0 | true | null | null | null | null | null | null | null | null | null | null |
null | null | liquid/lfm-2.5-2.6b:free | I20.0 | 1.09 | 110 | 216 | 0 | true | null | null | null | null | null | null | null | null | null | null |
null | null | liquid/lfm-2.5-2.6b:free | 290410006 | 0.71 | 102 | 166 | 0 | true | null | null | null | null | null | null | null | null | null | null |
null | null | liquid/lfm-2.5-2.6b:free | 6 | 2.64 | 107 | 536 | 0 | true | null | null | null | null | null | null | null | null | null | null |
null | null | liquid/lfm-2.5-2.6b:free | 183 | 0.75 | 132 | 184 | 0 | true | null | null | null | null | null | null | null | null | null | null |
null | null | liquid/lfm-2.5-2.6b:free | 70 | 1.69 | 105 | 192 | 0 | true | null | null | null | null | null | null | null | null | null | null |
null | null | liquid/lfm-2.5-2.6b:free | 18 | 1.64 | 106 | 451 | 0 | true | null | null | null | null | null | null | null | null | null | null |
null | null | liquid/lfm-2.5-2.6b:free | prothrombin complex concentrate (PCC) | 1.38 | 115 | 440 | 0 | true | null | null | null | null | null | null | null | null | null | null |
null | null | liquid/lfm-2.5-2.6b:free | NO | 1.06 | 114 | 191 | 0 | true | null | null | null | null | null | null | null | null | null | null |
null | null | liquid/lfm-2.5-2.6b:free | high | 1.04 | 100 | 228 | 0 | true | null | null | null | null | null | null | null | null | null | null |
onc_staging | Oncology staging | liquid/lfm-2.5-2.6b:free | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
cardio_gdm | Cardiology guideline | liquid/lfm-2.5-2.6b:free | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
ddi_warfarin | Drug-drug interaction | liquid/lfm-2.5-2.6b:free | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
rare_bone | Rare-disease workup | liquid/lfm-2.5-2.6b:free | null | null | null | null | null | null | null | null | null | 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 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
onc_staging | Oncology staging | nvidia/nemotron-3-ultra-550b-a55b:free | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
cardio_gdm | Cardiology guideline | nvidia/nemotron-3-ultra-550b-a55b:free | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
ddi_warfarin | Drug-drug interaction | nvidia/nemotron-3-ultra-550b-a55b:free | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
rare_bone | Rare-disease workup | nvidia/nemotron-3-ultra-550b-a55b:free | null | null | null | null | null | null | null | null | null | 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 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
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