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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 7 new columns ({'brain_rsa_Sem', 'brain_rsa_mean', 'brain_rsa_Phon', 'brain_rsa_pearson_mean', 'frac_of_ceiling_mean', 'brain_rsa_std', 'brain_n_cells'}) and 9 missing columns ({'dataset', 'rsa_pearson', 'session', 'rsa_kendall', 'rsa', 'n_stim', 'task', 'rsa_lo', 'rsa_hi'}).

This happened while the csv dataset builder was generating data using

hf://datasets/BrainAlign/cdl-devai-lytle2020/by-model/parc-mamba-seed0/checkpoints.csv (at revision 401d1af39118d7354bdad90f5daf998289dec991), ['hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-mamba-seed0/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-mamba-seed0/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-mamba-seed1/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-mamba-seed1/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-mamba-seed2/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-mamba-seed2/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-pythia-seed0/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-pythia-seed0/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-pythia-seed1/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-pythia-seed1/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-pythia-seed2/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-pythia-seed2/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-rwkv-seed0/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-rwkv-seed0/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-rwkv-seed1/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-rwkv-seed1/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-rwkv-seed2/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-rwkv-seed2/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/pythia-1.4b-full/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/pythia-1.4b-full/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/pythia-160m-full/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/pythia-160m-full/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/pythia-1b-full/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/pythia-1b-full/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/pythia-410m-full/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/pythia-410m-full/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/pythia-70m-full/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/pythia-70m-full/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/ceiling-analysis/ceilings.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/overall/by_checkpoint.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/overall/claim_tests.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/overall/null_referenced.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/overall/null_summary.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/overall/summary_by_family.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
              family: string
              model_ref: string
              step: int64
              tokens: int64
              brain_rsa_mean: double
              brain_rsa_std: double
              brain_rsa_pearson_mean: double
              brain_n_cells: int64
              frac_of_ceiling_mean: double
              brain_rsa_Phon: double
              brain_rsa_Sem: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1643
              to
              {'family': Value('string'), 'model_ref': Value('string'), 'dataset': Value('string'), 'step': Value('int64'), 'tokens': Value('int64'), 'task': Value('string'), 'session': Value('string'), 'n_stim': Value('int64'), 'rsa': Value('float64'), 'rsa_pearson': Value('float64'), 'rsa_kendall': Value('float64'), 'rsa_lo': Value('float64'), 'rsa_hi': 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 7 new columns ({'brain_rsa_Sem', 'brain_rsa_mean', 'brain_rsa_Phon', 'brain_rsa_pearson_mean', 'frac_of_ceiling_mean', 'brain_rsa_std', 'brain_n_cells'}) and 9 missing columns ({'dataset', 'rsa_pearson', 'session', 'rsa_kendall', 'rsa', 'n_stim', 'task', 'rsa_lo', 'rsa_hi'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/BrainAlign/cdl-devai-lytle2020/by-model/parc-mamba-seed0/checkpoints.csv (at revision 401d1af39118d7354bdad90f5daf998289dec991), ['hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-mamba-seed0/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-mamba-seed0/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-mamba-seed1/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-mamba-seed1/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-mamba-seed2/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-mamba-seed2/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-pythia-seed0/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-pythia-seed0/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-pythia-seed1/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-pythia-seed1/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-pythia-seed2/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-pythia-seed2/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-rwkv-seed0/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-rwkv-seed0/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-rwkv-seed1/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-rwkv-seed1/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-rwkv-seed2/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/parc-rwkv-seed2/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/pythia-1.4b-full/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/pythia-1.4b-full/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/pythia-160m-full/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/pythia-160m-full/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/pythia-1b-full/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/pythia-1b-full/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/pythia-410m-full/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/pythia-410m-full/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/pythia-70m-full/brain_alignment.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/by-model/pythia-70m-full/checkpoints.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/ceiling-analysis/ceilings.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/overall/by_checkpoint.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/overall/claim_tests.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/overall/null_referenced.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/overall/null_summary.csv', 'hf://datasets/BrainAlign/cdl-devai-lytle2020@401d1af39118d7354bdad90f5daf998289dec991/overall/summary_by_family.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.

family
string
model_ref
string
dataset
string
step
int64
tokens
int64
task
string
session
string
n_stim
int64
rsa
float64
rsa_pearson
float64
rsa_kendall
float64
rsa_lo
null
rsa_hi
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-10
ds002236
10
5,242,880
Phon
ses-11
96
0.016661
0.010744
0.011087
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-20
ds002236
20
10,485,760
Phon
ses-11
96
0.021726
0.020761
0.014714
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-30
ds002236
30
15,728,640
Phon
ses-11
96
0.013485
0.013985
0.008961
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-50
ds002236
50
26,214,400
Phon
ses-11
96
0.01033
0.010138
0.006908
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-70
ds002236
70
36,700,160
Phon
ses-11
96
-0.013673
-0.01543
-0.009085
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-100
ds002236
100
52,428,800
Phon
ses-11
96
0.013548
-0.003417
0.008704
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-300
ds002236
300
157,286,400
Phon
ses-11
96
0.002967
0.001615
0.002026
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-640
ds002236
640
335,544,320
Phon
ses-11
96
0.044675
0.024745
0.02971
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-1100
ds002236
1,100
576,716,800
Phon
ses-11
96
0.054989
0.030145
0.036664
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-1850
ds002236
1,850
969,932,800
Phon
ses-11
96
0.039608
0.024844
0.026448
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-4000
ds002236
4,000
2,097,152,000
Phon
ses-11
96
0.042966
0.017739
0.028961
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-10
ds002236
10
5,242,880
Phon
ses-11+
96
0.012069
0.006371
0.007957
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-20
ds002236
20
10,485,760
Phon
ses-11+
96
0.025447
0.019093
0.016936
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-30
ds002236
30
15,728,640
Phon
ses-11+
96
0.020536
0.0118
0.013716
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-50
ds002236
50
26,214,400
Phon
ses-11+
96
0.014607
0.010419
0.00975
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-70
ds002236
70
36,700,160
Phon
ses-11+
96
-0.024272
-0.012432
-0.016161
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-100
ds002236
100
52,428,800
Phon
ses-11+
96
-0.021863
-0.017995
-0.014469
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-300
ds002236
300
157,286,400
Phon
ses-11+
96
-0.013213
-0.009751
-0.008852
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-640
ds002236
640
335,544,320
Phon
ses-11+
96
0.027048
0.01058
0.018127
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-1100
ds002236
1,100
576,716,800
Phon
ses-11+
96
0.048945
0.017919
0.032835
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-1850
ds002236
1,850
969,932,800
Phon
ses-11+
96
0.036483
0.010722
0.024495
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-4000
ds002236
4,000
2,097,152,000
Phon
ses-11+
96
0.036467
0.00521
0.024534
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-10
ds002236
10
5,242,880
Phon
ses-9
96
-0.003713
-0.000105
-0.002449
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-20
ds002236
20
10,485,760
Phon
ses-9
96
0.011791
0.014668
0.007844
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-30
ds002236
30
15,728,640
Phon
ses-9
96
0.014603
0.011906
0.009742
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-50
ds002236
50
26,214,400
Phon
ses-9
96
0.012775
0.013132
0.008515
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-70
ds002236
70
36,700,160
Phon
ses-9
96
0.008179
-0.002864
0.005278
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-100
ds002236
100
52,428,800
Phon
ses-9
96
0.011124
-0.007351
0.007394
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-300
ds002236
300
157,286,400
Phon
ses-9
96
0.006252
-0.001618
0.004197
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-640
ds002236
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ses-9
96
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ds002236
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576,716,800
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ses-9
96
0.06946
0.030352
0.04652
null
null
parc-mamba-seed0
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ds002236
1,850
969,932,800
Phon
ses-9
96
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0.038378
null
null
parc-mamba-seed0
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ds002236
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2,097,152,000
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ses-9
96
0.052671
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ds002236
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ses-11
48
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ds002236
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10,485,760
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48
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parc-mamba-seed0
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ds002236
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48
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parc-mamba-seed0
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26,214,400
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parc-mamba-seed0
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ds002236
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36,700,160
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parc-mamba-seed0
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ds002236
100
52,428,800
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ses-11
48
0.037733
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null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-300
ds002236
300
157,286,400
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ses-11
48
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parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-640
ds002236
640
335,544,320
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48
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null
null
parc-mamba-seed0
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ds002236
1,100
576,716,800
Sem
ses-11
48
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parc-mamba-seed0
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969,932,800
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parc-mamba-seed0
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ds002236
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2,097,152,000
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ses-11
48
0.004193
0.014519
0.002822
null
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parc-mamba-seed0
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ds002236
10
5,242,880
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48
0.025989
-0.009294
0.017756
null
null
parc-mamba-seed0
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ds002236
20
10,485,760
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ses-11+
48
0.025982
0.001143
0.018237
null
null
parc-mamba-seed0
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ds002236
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15,728,640
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ses-11+
48
0.021837
0.008954
0.014534
null
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parc-mamba-seed0
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ds002236
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26,214,400
Sem
ses-11+
48
0.022951
-0.004146
0.01499
null
null
parc-mamba-seed0
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ds002236
70
36,700,160
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48
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null
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parc-mamba-seed0
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ds002236
100
52,428,800
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48
0.022892
-0.000945
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null
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parc-mamba-seed0
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ds002236
300
157,286,400
Sem
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48
-0.026502
0.011487
-0.016912
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-640
ds002236
640
335,544,320
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48
0.03695
0.003353
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null
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parc-mamba-seed0
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ds002236
1,100
576,716,800
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48
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parc-mamba-seed0
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ds002236
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48
-0.00152
0.005968
-0.001035
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parc-mamba-seed0
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ds002236
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2,097,152,000
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ses-11+
48
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-0.00363
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parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-10
ds002236
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null
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parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-20
ds002236
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10,485,760
Sem
ses-9
48
0.038496
0.016817
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null
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parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-30
ds002236
30
15,728,640
Sem
ses-9
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null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-50
ds002236
50
26,214,400
Sem
ses-9
48
0.011268
0.008062
0.007665
null
null
parc-mamba-seed0
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70
36,700,160
Sem
ses-9
48
-0.006103
0.007816
-0.003987
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-100
ds002236
100
52,428,800
Sem
ses-9
48
0.015104
0.004521
0.00993
null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-300
ds002236
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157,286,400
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-0.013941
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-0.009235
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parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-640
ds002236
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335,544,320
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parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-1100
ds002236
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576,716,800
Sem
ses-9
48
0.028048
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null
null
parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-1850
ds002236
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969,932,800
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ses-9
48
-0.011678
0.006343
-0.008178
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parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-4000
ds002236
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-0.014933
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parc-mamba-seed0
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parc-mamba-seed0
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10,485,760
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null
null
null
null
parc-mamba-seed0
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null
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26,214,400
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null
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36,700,160
null
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null
null
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parc-mamba-seed0
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52,428,800
null
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null
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parc-mamba-seed0
jmichaelov/parc-mamba-seed0@checkpoint-300
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157,286,400
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jmichaelov/parc-mamba-seed0@checkpoint-640
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null
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parc-mamba-seed0
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parc-mamba-seed0
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969,932,800
null
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parc-mamba-seed0
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parc-mamba-seed1
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ds002236
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ses-11
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parc-mamba-seed1
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ds002236
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10,485,760
Phon
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null
null
parc-mamba-seed1
jmichaelov/parc-mamba-seed1@checkpoint-30
ds002236
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ses-11
96
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parc-mamba-seed1
jmichaelov/parc-mamba-seed1@checkpoint-50
ds002236
50
26,214,400
Phon
ses-11
96
0.011751
0.00553
0.008036
null
null
parc-mamba-seed1
jmichaelov/parc-mamba-seed1@checkpoint-70
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36,700,160
Phon
ses-11
96
0.040887
-0.004932
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null
null
parc-mamba-seed1
jmichaelov/parc-mamba-seed1@checkpoint-100
ds002236
100
52,428,800
Phon
ses-11
96
0.035421
0.006134
0.023811
null
null
parc-mamba-seed1
jmichaelov/parc-mamba-seed1@checkpoint-300
ds002236
300
157,286,400
Phon
ses-11
96
0.017808
0.002124
0.011863
null
null
parc-mamba-seed1
jmichaelov/parc-mamba-seed1@checkpoint-640
ds002236
640
335,544,320
Phon
ses-11
96
0.013388
0.018665
0.008877
null
null
parc-mamba-seed1
jmichaelov/parc-mamba-seed1@checkpoint-1100
ds002236
1,100
576,716,800
Phon
ses-11
96
0.027568
0.019309
0.018531
null
null
parc-mamba-seed1
jmichaelov/parc-mamba-seed1@checkpoint-1850
ds002236
1,850
969,932,800
Phon
ses-11
96
0.026263
0.017583
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null
null
parc-mamba-seed1
jmichaelov/parc-mamba-seed1@checkpoint-4000
ds002236
4,000
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Phon
ses-11
96
0.033036
0.01807
0.02217
null
null
parc-mamba-seed1
jmichaelov/parc-mamba-seed1@checkpoint-10
ds002236
10
5,242,880
Phon
ses-11+
96
0.01034
0.006411
0.0068
null
null
parc-mamba-seed1
jmichaelov/parc-mamba-seed1@checkpoint-20
ds002236
20
10,485,760
Phon
ses-11+
96
0.018306
0.012691
0.012305
null
null
parc-mamba-seed1
jmichaelov/parc-mamba-seed1@checkpoint-30
ds002236
30
15,728,640
Phon
ses-11+
96
0.008219
0.004767
0.005632
null
null
parc-mamba-seed1
jmichaelov/parc-mamba-seed1@checkpoint-50
ds002236
50
26,214,400
Phon
ses-11+
96
0.018535
0.008751
0.012363
null
null
parc-mamba-seed1
jmichaelov/parc-mamba-seed1@checkpoint-70
ds002236
70
36,700,160
Phon
ses-11+
96
0.0578
-0.00093
0.038721
null
null
parc-mamba-seed1
jmichaelov/parc-mamba-seed1@checkpoint-100
ds002236
100
52,428,800
Phon
ses-11+
96
0.027087
-0.008471
0.018444
null
null
parc-mamba-seed1
jmichaelov/parc-mamba-seed1@checkpoint-300
ds002236
300
157,286,400
Phon
ses-11+
96
0.00752
-0.006043
0.00493
null
null
parc-mamba-seed1
jmichaelov/parc-mamba-seed1@checkpoint-640
ds002236
640
335,544,320
Phon
ses-11+
96
0.000214
0.005605
0.000183
null
null
parc-mamba-seed1
jmichaelov/parc-mamba-seed1@checkpoint-1100
ds002236
1,100
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Phon
ses-11+
96
0.028529
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0.01958
null
null
parc-mamba-seed1
jmichaelov/parc-mamba-seed1@checkpoint-1850
ds002236
1,850
969,932,800
Phon
ses-11+
96
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0.015191
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null
null
parc-mamba-seed1
jmichaelov/parc-mamba-seed1@checkpoint-4000
ds002236
4,000
2,097,152,000
Phon
ses-11+
96
0.032477
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0.021944
null
null
parc-mamba-seed1
jmichaelov/parc-mamba-seed1@checkpoint-10
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Phon
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End of preview.

Lytle et al. (2020) — LM brain-alignment results

Language-model / fMRI representational-alignment results for Lytle et al. (2020): orthographic, phonological and semantic word processing in school-aged children (8.7-15.5), auditory and visual

OpenNeuro accession ds002236 · cohort: school-aged children, ages 8.7-15.5 · modality: auditory and visual · tasks: Phon, Sem · cells: 6 · rows: 924

Layout follows BrainAlign/cdl-devai-results: by-model/<family>/{brain_alignment,checkpoints}.csv, overall/, ceiling-analysis/, provenance_tier_ledger.json.

Result: alignment is not distinguishable from a random seed

5 trained families (pythia-1.4b-full, pythia-160m-full, pythia-1b-full, pythia-410m-full, pythia-70m-full) and 9 PARC noise-seed baselines, scored identically. Cells where a real family exceeds all 9 noise seeds: 0 of 30, against 3.0 expected by chance.

Pooled across all three developmental datasets: 9/130 observed vs 13.0 expected (p = 0.91); per-cell means of real families vs noise seeds correlate at r = +0.863; 83.9% of variance is cell identity and 3.2% model family.

Interpretation

These RDMs have real inter-subject reliability (noise ceilings in ceiling-analysis/ceilings.csv), but the upstream pipeline's positive controls fail on this dataset. The claim supported here is "no LM alignment is detectable by this measurement"not "language models do not align with the developing brain." Read this as a result about the benchmark.

Negative results are published here deliberately: the per-cell nulls and the noise-seed baselines are the reusable part.

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