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The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      Schema at index 1 was different: 
effort: string
reasoning_tokens: int64
completion_tokens: int64
prompt_tokens: int64
n_findings: int64
latency_s: double
vs
repo: string
source: string
github: string
commit: string
reasoning_effort: string
backend: string
model: string
latency_s: double
usage: struct<prompt_tokens: int64, completion_tokens: int64, reasoning_tokens: int64, total_tokens: int64>
pack: struct<files: int64, approx_tokens: int64, total_chars: int64, prompt_blob_chars: int64, max_chars: int64>
summary: string
findings: list<item: null>
n_findings: int64
verified_findings: list<item: null>
n_verified: int64
notes: string
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 244, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4645, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2866, in _head
                  return next(iter(self.iter(batch_size=n)))
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 3073, in iter
                  for key, pa_table in ex_iterable.iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2581, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 589, in _iter_arrow
                  yield new_key, pa.Table.from_batches(chunks_buffer)
                                 ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^
                File "pyarrow/table.pxi", line 5012, in pyarrow.lib.Table.from_batches
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                  return check_status(status)
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowInvalid: Schema at index 1 was different: 
              effort: string
              reasoning_tokens: int64
              completion_tokens: int64
              prompt_tokens: int64
              n_findings: int64
              latency_s: double
              vs
              repo: string
              source: string
              github: string
              commit: string
              reasoning_effort: string
              backend: string
              model: string
              latency_s: double
              usage: struct<prompt_tokens: int64, completion_tokens: int64, reasoning_tokens: int64, total_tokens: int64>
              pack: struct<files: int64, approx_tokens: int64, total_chars: int64, prompt_blob_chars: int64, max_chars: int64>
              summary: string
              findings: list<item: null>
              n_findings: int64
              verified_findings: list<item: null>
              n_verified: int64
              notes: string

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RepoTruth Findings

Structured documentation-vs-code contradiction findings from RepoTruth using Reflection Beam-1.0-501B-A23B (OpenAI-compatible API at https://api.reflection.ai/openai/v1).

What each row is

One audited repository (fixture or public GitHub clone), with:

  • summary, findings_json (verified true positives for real repos)
  • Measured prompt_tokens, reasoning_tokens, completion_tokens, total_tokens, latency_s
  • reasoning_effort, model, source, optional github + commit
  • reasoning_tokens_per_finding when n_findings > 0

Honest thrift measurement (tinyclick effort sweep)

Same 3 planted findings recovered at every effort:

effort reasoning_tokens completion_tokens latency_s
low 246 703 4.29
medium 572 1157 7.22
high 580 1079 7.09

Claim we make: on this fixture, reasoning_effort=low used 57% fewer reasoning tokens than medium for the same verified findings. We do not claim a cross-model ~3× figure from this dataset alone.

Real OSS (verified TPs only)

repo verified findings prompt reasoning latency_s
encode/httpcore 5 56,742 4,292 36.53
pallets/itsdangerous 1 40,291 2,859 20.99
psf/requests 1 62,572 2,967 24.46
Kludex/starlette 1 76,850 2,252 21.37
pallets/click 0 70,244 2,943 25.35

Affiliation: Green Robin Labs. Entry for Hugging Face × Reflection Build with Beam.

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