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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)

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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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