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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_was_wrong', 'gp_flagged', 'escalated'}) and 14 missing columns ({'model', 'answer', 'call_error', 'seconds', 'cached', 'hedges', 'unsafe_claims', 'prompt_tokens', 'bonus_hits', 'refused', 'words', 'reading_grade', 'missed', 'completion_tokens'}).

This happened while the csv dataset builder was generating data using

hf://datasets/richardyoung/lab04-gp-vs-specialist/cascade.csv (at revision a40d0c6cc3b3b415b2b7e577860ecad682a9a33e), ['hf://datasets/richardyoung/lab04-gp-vs-specialist@a40d0c6cc3b3b415b2b7e577860ecad682a9a33e/answers.csv', 'hf://datasets/richardyoung/lab04-gp-vs-specialist@a40d0c6cc3b3b415b2b7e577860ecad682a9a33e/cascade.csv', 'hf://datasets/richardyoung/lab04-gp-vs-specialist@a40d0c6cc3b3b415b2b7e577860ecad682a9a33e/partA_temperature_sweep.csv', 'hf://datasets/richardyoung/lab04-gp-vs-specialist@a40d0c6cc3b3b415b2b7e577860ecad682a9a33e/per_question.csv', 'hf://datasets/richardyoung/lab04-gp-vs-specialist@a40d0c6cc3b3b415b2b7e577860ecad682a9a33e/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_was_wrong', 'gp_flagged', 'escalated'}) and 14 missing columns ({'model', 'answer', 'call_error', 'seconds', 'cached', 'hedges', 'unsafe_claims', 'prompt_tokens', 'bonus_hits', 'refused', 'words', 'reading_grade', 'missed', 'completion_tokens'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/richardyoung/lab04-gp-vs-specialist/cascade.csv (at revision a40d0c6cc3b3b415b2b7e577860ecad682a9a33e), ['hf://datasets/richardyoung/lab04-gp-vs-specialist@a40d0c6cc3b3b415b2b7e577860ecad682a9a33e/answers.csv', 'hf://datasets/richardyoung/lab04-gp-vs-specialist@a40d0c6cc3b3b415b2b7e577860ecad682a9a33e/cascade.csv', 'hf://datasets/richardyoung/lab04-gp-vs-specialist@a40d0c6cc3b3b415b2b7e577860ecad682a9a33e/partA_temperature_sweep.csv', 'hf://datasets/richardyoung/lab04-gp-vs-specialist@a40d0c6cc3b3b415b2b7e577860ecad682a9a33e/per_question.csv', 'hf://datasets/richardyoung/lab04-gp-vs-specialist@a40d0c6cc3b3b415b2b7e577860ecad682a9a33e/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
6.42
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
The four drug classes that constitute guideline-directed medical therapy (GDMT) for HFrEF are: 1. **ACE inhibitors** (or ARBs/ARNIs if ACEi contraindicated) 2. **Beta-blockers** (e.g., carvedilol, metoprolol succinate, bisoprolol) 3. **Mineralocorticoid receptor antagonists** (e.g., spironolactone, eplerenone) 4. **SG...
3.07
122
897
0
false
null
1
1
null
null
null
true
false
138
13.1
ddi_warfarin
Drug-drug interaction
liquid/lfm-2.5-2.6b:free
**Interaction Analysis** **1. Fluconazole + Warfarin** - Fluconazole is a moderate inhibitor of CYP2C9, the primary enzyme responsible for metabolizing S-warfarin (the more active enantiomer). - Inhibition of CYP2C9 by fluconazole leads to increased warfarin plasma concentrations and elevated INR. - Clinical consequen...
8.66
120
1,673
0
false
null
1
1
null
null
cyp2c9|cyp3a4
true
false
310
12.2
rare_bone
Rare-disease workup
liquid/lfm-2.5-2.6b:free
**Most Likely Diagnosis:** Autosomal dominant osteopetrosis (ADOPT) **Genes Most Often Involved:** - **TP53** — the most common cause (~50% of cases); accounts for the majority of autosomal dominant forms - Other genes (less common): *LRRC1* (autosomal recessive), *SLC37A3* (autosomal dominant), *NCOA4* (autosomal dom...
2.14
119
569
0
false
null
0.333
0
osteogenesis imperfecta|col1a1
null
autosomal dominant
true
false
140
36.7
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')]<|tool_call_end|>
0.99
144
192
0
false
null
0.5
0
granular
null
map
false
false
28
6.2
onc_staging
Oncology staging
nvidia/nemotron-3-ultra-550b-a55b:free
**T category: T2** (tumor >2 cm but ≤5 cm; 2.5 cm invasive ductal 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 Canc...
41.26
123
605
0
false
null
1
1
null
null
sentinel
false
false
53
13.8
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** (carvedilol, metoprolol succinate, bisoprolol) 3. **MRA** (spironolactone or eplerenone) 4. **SGLT2 inhibitor** (dapagliflozin or empagliflozin) **What to change ...
22.83
126
904
0
false
null
1
1
null
null
null
true
false
79
13.1
ddi_warfarin
Drug-drug interaction
nvidia/nemotron-3-ultra-550b-a55b:free
null
0.46
0
0
0
false
null
0
0
inr|bleed|clot|avoid
null
null
false
false
0
null
rare_bone
Rare-disease workup
nvidia/nemotron-3-ultra-550b-a55b:free
**Diagnosis:** Osteogenesis imperfecta (OI), most likely **Type I** (mild, autosomal dominant) given the combination of recurrent fractures, blue-grey sclerae, dentinogenesis imperfecta, and multi-generational inheritance. **Genes most often involved:** - **COL1A1** (17q21.33) – ~90% of pathogenic variants in domina...
6.8
120
400
0
false
null
1
1
null
null
autosomal dominant
true
false
120
15.2
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 source: NLM ICD-10-CM to SNOMED CT Map (2024 release).* ICD-10-CM is a statistical classification that groups clinically distinct conditions into single codes for billing and epidemiology (e.g., “without complications” is a re...
54.29
148
651
0
false
null
1
1
null
null
44054006|map
false
false
90
15.3
onc_staging
Oncology staging
~openai/gpt-astra-latest
Using **AJCC 8th-edition anatomic staging**, assuming the nodal metastases are **macrometastases (>2 mm)**: - **T2:** Tumor >2 cm but ≤5 cm (here, 2.5 cm). - **N1:** Metastases in 1–3 ipsilateral axillary nodes; specifically **pN1a(sn)** based on sentinel-node pathology. - **cM0:** No clinical or imaging evidence of d...
8.81
117
400
0.02117
false
null
1
1
null
null
sentinel
false
false
65
10.7
cardio_gdm
Cardiology guideline
~openai/gpt-astra-latest
The **2022 AHA/ACC/HFSA heart-failure guideline** recommends four foundational drug classes for HFrEF: 1. **Renin–angiotensin system inhibition:** preferably an **ARNI** (sacubitril/valsartan); an ACE inhibitor or ARB if ARNI is not feasible. 2. **Evidence-based β-blocker:** carvedilol, metoprolol **succinate**, or bi...
13.16
117
602
0.03127
false
null
1
1
null
null
titrate|potassium
true
false
162
13.2
ddi_warfarin
Drug-drug interaction
~openai/gpt-astra-latest
**Avoid St John’s wort, and arrange a warfarin-management plan before or promptly after starting fluconazole.** A stable INR of 2.4 does not protect against these interactions. | Combination | Mechanism and clinical consequence | |---|---| | **Fluconazole + warfarin** | Fluconazole inhibits **CYP2C9**, reducing cleara...
16.04
111
660
0.03411
false
null
1
1
null
null
cyp2c9|cyp3a4
true
false
252
14
rare_bone
Rare-disease workup
~openai/gpt-astra-latest
- **Most likely diagnosis:** **Osteogenesis imperfecta (OI), with autosomal dominant inheritance**—supported by recurrent low-trauma fractures, blue-grey sclerae, dentinogenesis imperfecta, and affected individuals across three generations. - **Genes most often involved:** **COL1A1** and **COL1A2**, encoding the α1 and...
6.63
111
266
0.01441
false
null
1
1
null
null
autosomal dominant
true
false
93
18.1
onto_map
Ontology mapping (ICD-10-CM to SNOMED CT)
~openai/gpt-astra-latest
**SNOMED CT:** *Type 2 diabetes mellitus without complication (disorder)* — **SCTID 313436004** — is the direct semantic match for **ICD-10-CM E11.9**; verify availability in your target SNOMED CT edition and release. ICD-10-CM groups diagnoses for classification and reporting, whereas SNOMED CT represents clinical me...
8.1
135
320
0.01735
false
null
1
1
null
null
map
true
false
82
14.3
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
48.9
60
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
24.1
60
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
24.3
60
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
25.7
60
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
28
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
6.42
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
3.07
null
897
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
8.66
null
1,673
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
2.14
null
569
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
0.99
null
192
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
41.26
null
605
0
null
null
1
1
null
null
null
null
null
null
null
cardio_gdm
Cardiology guideline
nvidia/nemotron-3-ultra-550b-a55b:free
null
22.83
null
904
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
0.46
null
0
0
null
null
0
0
null
null
null
null
null
null
null
rare_bone
Rare-disease workup
nvidia/nemotron-3-ultra-550b-a55b:free
null
6.8
null
400
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
54.29
null
651
0
null
null
1
1
null
null
null
null
null
null
null
onc_staging
Oncology staging
~openai/gpt-astra-latest
null
8.81
null
400
0.02117
null
null
1
1
null
null
null
null
null
null
null
cardio_gdm
Cardiology guideline
~openai/gpt-astra-latest
null
13.16
null
602
0.03127
null
null
1
1
null
null
null
null
null
null
null
ddi_warfarin
Drug-drug interaction
~openai/gpt-astra-latest
null
16.04
null
660
0.03411
null
null
1
1
null
null
null
null
null
null
null
rare_bone
Rare-disease workup
~openai/gpt-astra-latest
null
6.63
null
266
0.01441
null
null
1
1
null
null
null
null
null
null
null
onto_map
Ontology mapping (ICD-10-CM to SNOMED CT)
~openai/gpt-astra-latest
null
8.1
null
320
0.01735
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
17.1
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
14.3
null
null
~openai/gpt-astra-latest
null
null
null
null
null
null
null
1
1
null
null
null
null
null
null
14.1

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