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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
schema_version: int64
split: string
records: list<item: struct<generator: string, set_id: int64, seed: int64, variant: string, source: string, so (... 127 chars omitted)
  child 0, item: struct<generator: string, set_id: int64, seed: int64, variant: string, source: string, source_sha256 (... 115 chars omitted)
      child 0, generator: string
      child 1, set_id: int64
      child 2, seed: int64
      child 3, variant: string
      child 4, source: string
      child 5, source_sha256: string
      child 6, reference: string
      child 7, interval_ms: list<item: int64>
          child 0, item: int64
      child 8, output: string
      child 9, output_sha256: string
      child 10, objects: int64
source_documentation: string
results: list<item: struct<set_id: int64, status: string, source_url: string, archive: string, archive_bytes: (... 131 chars omitted)
  child 0, item: struct<set_id: int64, status: string, source_url: string, archive: string, archive_bytes: int64, arc (... 119 chars omitted)
      child 0, set_id: int64
      child 1, status: string
      child 2, source_url: string
      child 3, archive: string
      child 4, archive_bytes: int64
      child 5, archive_sha256: string
      child 6, files: list<item: struct<archive_name: string, local_name: string, bytes: int64, sha256: string>>
          child 0, item: struct<archive_name: string, local_name: string, bytes: int64, sha256: string>
              child 0, archive_name: string
              child 1, local_name: string
              child 2, bytes: int64
              child 3, sha256: string
source: string
selection_file: string
note: string
to
{'schema_version': Value('int64'), 'selection_file': Value('string'), 'source': Value('string'), 'source_documentation': Value('string'), 'note': Value('string'), 'results': List({'set_id': Value('int64'), 'status': Value('string'), 'source_url': Value('string'), 'archive': Value('string'), 'archive_bytes': Value('int64'), 'archive_sha256': Value('string'), 'files': List({'archive_name': Value('string'), 'local_name': Value('string'), 'bytes': Value('int64'), 'sha256': Value('string')})})}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 489, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              schema_version: int64
              split: string
              records: list<item: struct<generator: string, set_id: int64, seed: int64, variant: string, source: string, so (... 127 chars omitted)
                child 0, item: struct<generator: string, set_id: int64, seed: int64, variant: string, source: string, source_sha256 (... 115 chars omitted)
                    child 0, generator: string
                    child 1, set_id: int64
                    child 2, seed: int64
                    child 3, variant: string
                    child 4, source: string
                    child 5, source_sha256: string
                    child 6, reference: string
                    child 7, interval_ms: list<item: int64>
                        child 0, item: int64
                    child 8, output: string
                    child 9, output_sha256: string
                    child 10, objects: int64
              source_documentation: string
              results: list<item: struct<set_id: int64, status: string, source_url: string, archive: string, archive_bytes: (... 131 chars omitted)
                child 0, item: struct<set_id: int64, status: string, source_url: string, archive: string, archive_bytes: int64, arc (... 119 chars omitted)
                    child 0, set_id: int64
                    child 1, status: string
                    child 2, source_url: string
                    child 3, archive: string
                    child 4, archive_bytes: int64
                    child 5, archive_sha256: string
                    child 6, files: list<item: struct<archive_name: string, local_name: string, bytes: int64, sha256: string>>
                        child 0, item: struct<archive_name: string, local_name: string, bytes: int64, sha256: string>
                            child 0, archive_name: string
                            child 1, local_name: string
                            child 2, bytes: int64
                            child 3, sha256: string
              source: string
              selection_file: string
              note: string
              to
              {'schema_version': Value('int64'), 'selection_file': Value('string'), 'source': Value('string'), 'source_documentation': Value('string'), 'note': Value('string'), 'results': List({'set_id': Value('int64'), 'status': Value('string'), 'source_url': Value('string'), 'archive': Value('string'), 'archive_bytes': Value('int64'), 'archive_sha256': Value('string'), 'files': List({'archive_name': Value('string'), 'local_name': Value('string'), 'bytes': Value('int64'), 'sha256': Value('string')})})}
              because column names don't match

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YAML Metadata Warning:The task_categories "classification" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

osu-ai-detector reproducibility metadata v1.0.0

This release contains preregistered split definitions, exact source identities, acquisition records, verification hashes, generation revision records, and compact reference evaluation outputs for the osu-ai-detector technical report.

It intentionally excludes third-party raw beatmaps, audio, and upstream model weights. Researchers acquire those files from their original sources by using the published scripts, and the scripts reject files that do not match the registered identity.

Contents

  • manifests/: exact train, calibration, external, and disclosed final split identities and provenance.
  • reference-results/: aggregate frozen evaluation reports and completion seals; no per-sample secret identities are hidden in v1.0.0.
  • acquisition/: download and verification utilities copied from the research release.
  • DATA_INVENTORY.json: byte sizes and SHA-256 values for every released file.

All final blind-test identities are disclosed in this research release, as selected by the project owner after evaluation was completed.

Licensing boundary

Original metadata and derived tables authored by NettoAndTetto are CC BY 4.0. Third-party identifiers and factual provenance remain subject to applicable database and source-site terms. No license to third-party audio, beatmaps, artwork, or upstream weights is granted or implied.

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