The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: ArrowInvalid
Message: JSON parse error: Invalid value. in row 0
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 324, in _generate_tables
df = pandas_read_json(f)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
return pd.read_json(path_or_buf, **kwargs)
~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 815, in read_json
return json_reader.read()
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1014, in read
obj = self._get_object_parser(self.data)
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1040, in _get_object_parser
obj = FrameParser(json, **kwargs).parse()
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1176, in parse
self._parse()
~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1392, in _parse
ujson_loads(json, precise_float=self.precise_float), dtype=None
~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ValueError: Expected object or value
During handling of the above exception, another exception occurred:
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 4523, 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 2768, in _head
return next(iter(self.iter(batch_size=n)))
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2972, in iter
for key, pa_table in ex_iterable.iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2483, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, 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 327, in _generate_tables
raise e
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
pa_table = paj.read_json(
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
)
File "pyarrow/_json.pyx", line 364, in pyarrow._json.read_json
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: JSON parse error: Invalid value. in row 0Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Streetscape Representation
Research materials for Photographic representation sensitivity in multimodal streetscape auditing: a matched-panorama study in Singapore.
The release contains the 739-location source inventory, executable input-construction and inference code, 25,423 formal model-output records, analysis tables, seven main and six supplementary scientific figures, and reproducible validation modules.
The five configurations are local Qwen3.5-122B, Qwen3.5-397B and GLM-4.6V, alongside GPT-5.6-luna and GPT-5.6-sol accessed through a commercial API channel. The empirical study includes matched representations, balanced repeated controls, a directional panel, an additional 166-location spatial panel and matched prompt framing.
The validation materials include exact categorical-estimand checks, finite-repeat simulations, 420 single-attribute and 24 joint 12-attribute calibration scenarios, and an unchanged-inventory refresh application retaining all 252 comparisons. Simulations have known marginal probability targets; they are separate from the recorded model requests. The application reports fixed-allocation effects, uniform fixed-size allocation expectations, exact observed-panel assignment extrema and tolerance sensitivity.
Files
Streetscape_reproducibility.zip: code, model records, simulation trials, tables, figures, metadata and verification reports.metadata/source_inventory.csv: source locations and panorama metadata.release_manifest.json: release scope, hashes and verification information.DATA_RIGHTS_NOTICE.txt: licensing and source-imagery access information.
Reproduction
Extract the archive, install requirements.txt, and run:
python study/analysis/run_all.py --study-root study --out recomputed_analysis
python study/validation/pooling_calibration/verify_outputs.py
python study/validation/inventory_refresh/run_application.py --study study --out recomputed_inventory
python study/validation/inventory_refresh/verify_application.py --study study --out recomputed_inventory
python study/validation/estimand/run_validation.py --analysis-root study/analysis/outputs --out recomputed_estimand
Module READMEs provide complete simulation and figure-reconstruction commands. portable/DEPLOYMENT.txt describes model deployment, input preparation and inference. The calibration reports operating characteristics under its specified probability and dependence models; nominal intervals and the variation guard are diagnostic rather than universal guarantees.
Source imagery was obtained through Google Maps API. Source-image access and use follow provider terms. Research code, metadata and model-output records are distributed under CC BY 4.0; third-party software and models retain their respective licenses.
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