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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 2082 new columns ({'0.0833.19', '0.1429.51', '0.125.10', '0.1429.231', '0.0.154', '0.1.67', '0.0909.36', '0.0.151', '0.2.2', '0.0.339', '0.0.28', '0.0.449', '0.0.493', '0.0.458', '0.1429.70', '0.0.385', '0.0714.1', '0.0.916', '0.1429.139', '0.0.249', '0.125.96', '0.0.468', '0.1.7', '0.1667.25', '0.0.840', '0.0714.3', '0.0.662', '0.1429.80', '0.0.661', '0.1429.193', '0.1429.247', '0.2222.25', '0.0.839', '0.0.941', '0.0.342', '0.1.62', '0.1538.14', '0.0.21', '0.0.234', '0.0.218', '0.125.48', '0.1.49', '0.0.933', '0.1.34', '0.1429.96', '0.0.651', '0.1429.115', '0.1429.4', '0.125.8', '0.0.748', '0.1111.78', '0.4.1', '0.0.604', '0.0.18', '0.0.1081', '0.0.1094', '0.0.1032', '0.0.675', '0.1111.49', '0.125.49', '0.0.816', '0.1429.132', '0.0.331', '0.1429.242', '0.0.180', '0.0.72', '0.2857.28', '0.0.862', '0.0625.2', '0.1111.15', '0.125.66', '0.0.899', '0.1818', '0.0.227', '0.0.408', '0.0.642', '0.0909.25', '0.125.40', '0.0.125', '0.125.25', '0.0.474', '0.1429.20', '0.2222.21', '0.1111.61', '0.1111.3', '0.0.179', '0.1429.155', '0.1429.258', '0.0.328', '0.0.982', '0.1429.105', '0.0.997', '0.0.145', '0.1429.75', '0.1429.267', '0.1429.129', '0.0.942', '0.0.315', '0.0.63', '0.0.779', '0.0.429', '0.0.443', '0.1429.8', '0.125.28', '0.0.395', '0.0.841', '0.125.18', '0.0.336', '0.0.527', '0.1875.2', '0.2.36', '0.25', '0.0.722', '0.1.36', '0.0.475', '0.1.26', '0.0.255', '0.0.54', '0.0.975', '0.0.935', '0.0.993', '0.0.1076', '0.1.30', '0.0.762', '0.1429.67', '0.1429.252', '0.0.968', '0.0.561', '0.0.797', '0.0.73
...
2', '0.2143.1', '0.0.743', '0.0.629', '0.1429.117', '0.0.1040', '0.125.67', '0.0909.44', '0.0769.18', '0.0.196', '0.1429.218', '0.1875', '0.125.3', '0.0.55', '0.0.229', '0.0769.4', '0.0.303', '0.1429.19', '0.1.39', '0.0.513', '0.1429.165', '0.125.68', '0.0.419', '0.0.567', '0.0.43', '0.0.482', '0.0.667', '0.0.1054', '0.0833.2', '0.2222.9', '0.0.882', '0.0.729', '0.0.380', '0.0.1026', '0.0.1084', '0.0.1024', '0.0909.29', '0.1667.17', '0.1429.73', '0.0.37', '0.0.86', '0.0.664', '0.0.304', '0.0.1004', '0.0.480', '0.0.83', '0.0.792', '0.0.607', '0.0.456', '0.1429.204', '0.1429.169', '0.0.858', '0.1429.261', '0.0.730', '0.0.258', '0.0909.38', '0.0.1047', '0.1.14', '0.0.322', '0.1429.32', '0.0.753', '0.0.744', '0.1.4', '0.0.755', '0.125.53', '0.0.79', '0.0.994', '0.1429.157', '0.1111.24', '0.0.247', '0.0.608', '0.0.415', '0.0.830', '0.0625.3', '0.2.3', '0.1111.43', '0.1429.128', '0.0.741', '0.0.872', '0.2857.14', '0.1111.55', '0.0.856', '0.0909.45', '0.0.702', '0.0.445', '0.0.327', '0.0.925', '0.2857.11', '0.0.1099', '0.1429.71', '0.1429.287', '0.0.723', '0.0.870', '0.0.1056', '0.1538.21', '0.2.17', '0.0.1063', '0.0.842', '0.1429.137', '0.1.16', '0.2222.1', '0.0.1023', '0.0.610', '0.0.453', '0.0.139', '0.1333.9', '0.0.128', '0.125.61', '0.0.437', '0.1333.11', '0.0.292', '0.125.71', '0.0.221', '0.1429.40', '0.1429.87', '0.1111.32', '0.2857.44', '0.0833', '0.0.873', '0.1429.246', '0.0.793', '0.0.162', '0.1429.276', '0.1429.30', '0.0.948', '0.0.287', '0.0.135', '0.0.405', '0.1818.14'}) and 2 missing columns ({'aardvark', '2.39'}).
This happened while the csv dataset builder was generating data using
hf://datasets/natebranda/Adaptive_Fluency_Similarity_Matrices_and_Frequency_Table_for_Animals/Forager_phonological_matrix.csv (at revision 05643ae92cbdc09da89031ec391b82d4addf2633), ['hf://datasets/natebranda/Adaptive_Fluency_Similarity_Matrices_and_Frequency_Table_for_Animals@05643ae92cbdc09da89031ec391b82d4addf2633/Forager_Animal_Frequencies.csv', 'hf://datasets/natebranda/Adaptive_Fluency_Similarity_Matrices_and_Frequency_Table_for_Animals@05643ae92cbdc09da89031ec391b82d4addf2633/Forager_phonological_matrix.csv', 'hf://datasets/natebranda/Adaptive_Fluency_Similarity_Matrices_and_Frequency_Table_for_Animals@05643ae92cbdc09da89031ec391b82d4addf2633/Forager_semantic_matrix.csv', 'hf://datasets/natebranda/Adaptive_Fluency_Similarity_Matrices_and_Frequency_Table_for_Animals@05643ae92cbdc09da89031ec391b82d4addf2633/July28_Forager_Animal_Frequencies.csv', 'hf://datasets/natebranda/Adaptive_Fluency_Similarity_Matrices_and_Frequency_Table_for_Animals@05643ae92cbdc09da89031ec391b82d4addf2633/July28_Forager_Phonological_Matrix.csv', 'hf://datasets/natebranda/Adaptive_Fluency_Similarity_Matrices_and_Frequency_Table_for_Animals@05643ae92cbdc09da89031ec391b82d4addf2633/July28_Forager_Semantic_Matrix.csv', 'hf://datasets/natebranda/Adaptive_Fluency_Similarity_Matrices_and_Frequency_Table_for_Animals@05643ae92cbdc09da89031ec391b82d4addf2633/USE_frequencies.csv', 'hf://datasets/natebranda/Adaptive_Fluency_Similarity_Matrices_and_Frequency_Table_for_Animals@05643ae92cbdc09da89031ec391b82d4addf2633/USE_phonological_matrix.csv', 'hf://datasets/natebranda/Adaptive_Fluency_Similarity_Matrices_and_Frequency_Table_for_Animals@05643ae92cbdc09da89031ec391b82d4addf2633/USE_semantic_matrix.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 1837, 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 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
1.0: double
0.375: double
0.0: double
0.0.1: double
0.1429: double
0.1429.1: double
0.0.2: double
0.0.3: double
0.0.4: double
0.0.5: double
0.0.6: double
0.0909: double
0.0714: double
0.0714.1: double
0.1429.2: double
0.0.7: double
0.3: double
0.0.8: double
0.0.9: double
0.125: double
0.0.10: double
0.0.11: double
0.0.12: double
0.0.13: double
0.0.14: double
0.125.1: double
0.0.15: double
0.1429.3: double
0.0833: double
0.0.16: double
0.0.17: double
0.1: double
0.0.18: double
0.0.19: double
0.0.20: double
0.0.21: double
0.0.22: double
0.1.1: double
0.0.23: double
0.0909.1: double
0.0.24: double
0.0.25: double
0.0.26: double
0.0.27: double
0.0.28: double
0.0.29: double
0.0.30: double
0.0769: double
0.0909.2: double
0.0.31: double
0.1.2: double
0.0.32: double
0.0.33: double
0.0.34: double
0.0.35: double
0.0.36: double
0.0.37: double
0.125.2: double
0.2857: double
0.2308: double
0.25: double
0.2222: double
0.3.1: double
0.2857.1: double
0.125.3: double
0.2857.2: double
0.1667: double
0.4: double
0.25.1: double
0.0909.3: double
0.0.38: double
0.0.39: double
0.0.40: double
0.0.41: double
0.0.42: double
0.0.43: double
0.2857.3: double
0.0714.2: double
0.1429.4: double
0.0.44: double
0.0.45: double
0.0.46: double
0.0.47: double
0.0.48: double
0.0.49: double
0.0.50: double
0.125.4: double
0.0.51: double
0.125.5: double
0.0.52: double
0.0.53: double
0.125.6: double
0.0.54: double
0.2222.1: double
0.1429.5: double
0.25.2: double
0.1818: double
0.125.7: double
0.2222.2: double
0.1333: d
...
7: double
0.0.1058: double
0.0.1059: double
0.0.1060: double
0.0.1061: double
0.1.66: double
0.0769.20: double
0.1111.83: double
0.0.1062: double
0.0.1063: double
0.0.1064: double
0.1429.286: double
0.0.1065: double
0.0.1066: double
0.1818.35: double
0.0.1067: double
0.0.1068: double
0.125.100: double
0.0.1069: double
0.0.1070: double
0.0.1071: double
0.0.1072: double
0.0.1073: double
0.0.1074: double
0.0.1075: double
0.1429.287: double
0.1429.288: double
0.0.1076: double
0.0.1077: double
0.1429.289: double
0.3.4: double
0.1429.290: double
0.2857.44: double
0.4286.1: double
0.2.39: double
0.1538.22: double
0.1429.291: double
0.1429.292: double
0.0833.28: double
0.0.1078: double
0.0.1079: double
0.1111.84: double
0.0833.29: double
0.0.1080: double
0.0625.5: double
0.1429.293: double
0.0.1081: double
0.0.1082: double
0.1429.294: double
0.0.1083: double
0.0.1084: double
0.0833.30: double
0.0.1085: double
0.1.67: double
0.0.1086: double
0.1667.25: double
0.0.1087: double
0.0.1088: double
0.1111.85: double
0.0.1089: double
0.0.1090: double
0.0.1091: double
0.0.1092: double
0.125.101: double
0.0.1093: double
0.1818.36: double
0.1429.295: double
0.1111.86: double
0.0.1094: double
0.1.68: double
0.0.1095: double
0.0.1096: double
0.1.69: double
0.1111.87: double
0.0.1097: double
0.0.1098: double
0.1111.88: double
0.0.1099: double
0.0.1100: double
0.0.1101: double
0.1111.89: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 242342
to
{'aardvark': Value('string'), '2.39': 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 1683, 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 1839, 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 2082 new columns ({'0.0833.19', '0.1429.51', '0.125.10', '0.1429.231', '0.0.154', '0.1.67', '0.0909.36', '0.0.151', '0.2.2', '0.0.339', '0.0.28', '0.0.449', '0.0.493', '0.0.458', '0.1429.70', '0.0.385', '0.0714.1', '0.0.916', '0.1429.139', '0.0.249', '0.125.96', '0.0.468', '0.1.7', '0.1667.25', '0.0.840', '0.0714.3', '0.0.662', '0.1429.80', '0.0.661', '0.1429.193', '0.1429.247', '0.2222.25', '0.0.839', '0.0.941', '0.0.342', '0.1.62', '0.1538.14', '0.0.21', '0.0.234', '0.0.218', '0.125.48', '0.1.49', '0.0.933', '0.1.34', '0.1429.96', '0.0.651', '0.1429.115', '0.1429.4', '0.125.8', '0.0.748', '0.1111.78', '0.4.1', '0.0.604', '0.0.18', '0.0.1081', '0.0.1094', '0.0.1032', '0.0.675', '0.1111.49', '0.125.49', '0.0.816', '0.1429.132', '0.0.331', '0.1429.242', '0.0.180', '0.0.72', '0.2857.28', '0.0.862', '0.0625.2', '0.1111.15', '0.125.66', '0.0.899', '0.1818', '0.0.227', '0.0.408', '0.0.642', '0.0909.25', '0.125.40', '0.0.125', '0.125.25', '0.0.474', '0.1429.20', '0.2222.21', '0.1111.61', '0.1111.3', '0.0.179', '0.1429.155', '0.1429.258', '0.0.328', '0.0.982', '0.1429.105', '0.0.997', '0.0.145', '0.1429.75', '0.1429.267', '0.1429.129', '0.0.942', '0.0.315', '0.0.63', '0.0.779', '0.0.429', '0.0.443', '0.1429.8', '0.125.28', '0.0.395', '0.0.841', '0.125.18', '0.0.336', '0.0.527', '0.1875.2', '0.2.36', '0.25', '0.0.722', '0.1.36', '0.0.475', '0.1.26', '0.0.255', '0.0.54', '0.0.975', '0.0.935', '0.0.993', '0.0.1076', '0.1.30', '0.0.762', '0.1429.67', '0.1429.252', '0.0.968', '0.0.561', '0.0.797', '0.0.73
...
2', '0.2143.1', '0.0.743', '0.0.629', '0.1429.117', '0.0.1040', '0.125.67', '0.0909.44', '0.0769.18', '0.0.196', '0.1429.218', '0.1875', '0.125.3', '0.0.55', '0.0.229', '0.0769.4', '0.0.303', '0.1429.19', '0.1.39', '0.0.513', '0.1429.165', '0.125.68', '0.0.419', '0.0.567', '0.0.43', '0.0.482', '0.0.667', '0.0.1054', '0.0833.2', '0.2222.9', '0.0.882', '0.0.729', '0.0.380', '0.0.1026', '0.0.1084', '0.0.1024', '0.0909.29', '0.1667.17', '0.1429.73', '0.0.37', '0.0.86', '0.0.664', '0.0.304', '0.0.1004', '0.0.480', '0.0.83', '0.0.792', '0.0.607', '0.0.456', '0.1429.204', '0.1429.169', '0.0.858', '0.1429.261', '0.0.730', '0.0.258', '0.0909.38', '0.0.1047', '0.1.14', '0.0.322', '0.1429.32', '0.0.753', '0.0.744', '0.1.4', '0.0.755', '0.125.53', '0.0.79', '0.0.994', '0.1429.157', '0.1111.24', '0.0.247', '0.0.608', '0.0.415', '0.0.830', '0.0625.3', '0.2.3', '0.1111.43', '0.1429.128', '0.0.741', '0.0.872', '0.2857.14', '0.1111.55', '0.0.856', '0.0909.45', '0.0.702', '0.0.445', '0.0.327', '0.0.925', '0.2857.11', '0.0.1099', '0.1429.71', '0.1429.287', '0.0.723', '0.0.870', '0.0.1056', '0.1538.21', '0.2.17', '0.0.1063', '0.0.842', '0.1429.137', '0.1.16', '0.2222.1', '0.0.1023', '0.0.610', '0.0.453', '0.0.139', '0.1333.9', '0.0.128', '0.125.61', '0.0.437', '0.1333.11', '0.0.292', '0.125.71', '0.0.221', '0.1429.40', '0.1429.87', '0.1111.32', '0.2857.44', '0.0833', '0.0.873', '0.1429.246', '0.0.793', '0.0.162', '0.1429.276', '0.1429.30', '0.0.948', '0.0.287', '0.0.135', '0.0.405', '0.1818.14'}) and 2 missing columns ({'aardvark', '2.39'}).
This happened while the csv dataset builder was generating data using
hf://datasets/natebranda/Adaptive_Fluency_Similarity_Matrices_and_Frequency_Table_for_Animals/Forager_phonological_matrix.csv (at revision 05643ae92cbdc09da89031ec391b82d4addf2633), ['hf://datasets/natebranda/Adaptive_Fluency_Similarity_Matrices_and_Frequency_Table_for_Animals@05643ae92cbdc09da89031ec391b82d4addf2633/Forager_Animal_Frequencies.csv', 'hf://datasets/natebranda/Adaptive_Fluency_Similarity_Matrices_and_Frequency_Table_for_Animals@05643ae92cbdc09da89031ec391b82d4addf2633/Forager_phonological_matrix.csv', 'hf://datasets/natebranda/Adaptive_Fluency_Similarity_Matrices_and_Frequency_Table_for_Animals@05643ae92cbdc09da89031ec391b82d4addf2633/Forager_semantic_matrix.csv', 'hf://datasets/natebranda/Adaptive_Fluency_Similarity_Matrices_and_Frequency_Table_for_Animals@05643ae92cbdc09da89031ec391b82d4addf2633/July28_Forager_Animal_Frequencies.csv', 'hf://datasets/natebranda/Adaptive_Fluency_Similarity_Matrices_and_Frequency_Table_for_Animals@05643ae92cbdc09da89031ec391b82d4addf2633/July28_Forager_Phonological_Matrix.csv', 'hf://datasets/natebranda/Adaptive_Fluency_Similarity_Matrices_and_Frequency_Table_for_Animals@05643ae92cbdc09da89031ec391b82d4addf2633/July28_Forager_Semantic_Matrix.csv', 'hf://datasets/natebranda/Adaptive_Fluency_Similarity_Matrices_and_Frequency_Table_for_Animals@05643ae92cbdc09da89031ec391b82d4addf2633/USE_frequencies.csv', 'hf://datasets/natebranda/Adaptive_Fluency_Similarity_Matrices_and_Frequency_Table_for_Animals@05643ae92cbdc09da89031ec391b82d4addf2633/USE_phonological_matrix.csv', 'hf://datasets/natebranda/Adaptive_Fluency_Similarity_Matrices_and_Frequency_Table_for_Animals@05643ae92cbdc09da89031ec391b82d4addf2633/USE_semantic_matrix.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.
aardvark string | 2.39 float64 |
|---|---|
aardwolf | 1.11 |
abalone | 2.66 |
abeja | 0.0001 |
addax | 1.33 |
adder | 2.69 |
adelgid | 1.32 |
adelie penguin | 1.8 |
aedes aegypti | 1.97 |
affenpinscher | 0.0001 |
afghan hound | 3.29 |
african dog | 4.64 |
african elephant | 4.01 |
african wild dog | 4.41 |
agama | 1.98 |
agouti | 1.88 |
airedale terrier | 1.99 |
akita | 2.49 |
albacore | 2.23 |
albatross | 2.9 |
albino python | 2.98 |
alga | 2.33 |
alligator | 3.32 |
alligator lizard | 3.15 |
alligator snapping turtle | 3.03 |
allosaurus | 1.85 |
alpaca | 2.8 |
amberjack | 1.64 |
american toad | 3.34 |
amoeba | 2.64 |
amphibian | 2.72 |
amphioxus | 1.25 |
amphipod | 1.72 |
anaconda | 2.97 |
anchovy | 2.58 |
anemone | 2.56 |
angelfish | 1.95 |
anglerfish | 1.61 |
angora goat | 2.57 |
angora rabbit | 2.58 |
anhinga | 1.31 |
ankylosaur | 1.13 |
annelid | 1.58 |
anole | 1.55 |
ant | 3.86 |
anteater | 2.28 |
antelope | 3.08 |
antelope squirrel | 2.98 |
anthropoid | 2.11 |
antlion | 1.29 |
apatosaurus | 1.53 |
ape | 3.48 |
aphid | 2.39 |
aplysia | 1.7 |
appaloosa | 1.93 |
apple maggot | 2.78 |
arachnid | 2.31 |
arapaima | 1.34 |
archaea | 2.3 |
archeopteryx | 0.0001 |
archosaur | 0.0001 |
arctic char | 3.36 |
arctic fox | 3.94 |
argali | 1.03 |
armadillo | 2.7 |
armyworm | 1.6 |
arrowhead dogfish | 2.21 |
arrowhead shark | 2.84 |
arthropod | 2.33 |
ascidians | 1.41 |
asian elephant | 3.98 |
asp | 3.05 |
ass | 5 |
assassin bug | 3.55 |
auk | 2.27 |
auklet | 0.0001 |
auroch | 1.05 |
australopithecine | 1.4 |
avian | 3.14 |
avocet | 1.83 |
axolotl | 2.02 |
aye aye | 3.59 |
babirusa | 1.04 |
baboon | 2.73 |
baby | 5.26 |
baca | 2.73 |
bacteria | 4.19 |
badger | 3.48 |
bald eagle | 3.65 |
baleen whale | 2.09 |
banana slug | 3.23 |
bandicoot | 2.51 |
bantam | 2.79 |
bark beetle | 3.36 |
barn owl | 3.63 |
barnacle | 2.55 |
barnacle goose | 2.53 |
barracuda | 2.78 |
barramundi | 1.89 |
barred owl | 3.48 |
basenji | 1.56 |
End of preview.
The contents of this dataset are from the Forager computer program. Its interactive interface can be found at https://forager.research.bowdoin.edu. Please read the LICENSE file in this data set and check for further information on the Forager GitHub repository (https://github.com/thelexiconlab/forager-web) in addition to the docs tab of the web interface linked above.
Citation:
Kumar, A.A., Apsel, M., Zhang, L., Xing, N., Jones. M.N. (2023). forager: A Python package and web interface for modeling mental search
Kumar, A.A., Lundin, N. B., Jones, M.N. (2022). Mouse-mole-vole: The inconspicuous benefits of phonology during retrieval from semantic memory. In Proceedings of the 44th Annual Meeting of the Cognitive Science Society.
Hills, T. T., Jones, M. N., & Todd, P. M. (2012). Optimal foraging in semantic memory. Psychological Review, 119(2), 431.
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