BUG: Inconsistent behavior while constructing a Series with large integers in a int64 masked array

[MridulS]

Pandas version checks

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

In [1]: import pandas as pd

In [2]: import numpy.ma as ma

In [3]: mx = ma.masked_array([4873214862074861312, 4875446630161458944, 4824652147895424384, 0, 3526420114272476800], mask=[0, 0, 0, 1, 0])

In [4]: pd.Series(mx, dtype='Int64')
Out[4]: 
0    4873214862074861568
1    4875446630161459200
2    4824652147895424000
3                   <NA>
4    3526420114272476672
dtype: Int64

In [5]: mx.data - pd.Series(mx, dtype='Int64')
Out[5]: 
0    -256
1    -256
2     384
3    <NA>
4     128
dtype: Int64

Issue Description

While creating a series object from a masked array of large-ish integers (less than max of Int64), the output doesn't match the input. This has probably something to do with float downcast/upcast somewhere.

Probably related (?) #30268, #50757

Expected Behavior

mx.data - pd.Series(mx, dtype='Int64') should be all zero with <NA> for the mask.

Installed Versions

INSTALLED VERSIONS

commit : a671b5a
python : 3.11.6.final.0
python-bits : 64
OS : Darwin
OS-release : 23.2.0
Version : Darwin Kernel Version 23.2.0: Wed Nov 15 21:53:18 PST 2023; root:xnu-10002.61.3~2/RELEASE_ARM64_T6000
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 2.1.4
numpy : 1.26.1
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 68.2.2
pip : 23.3.1
Cython : 3.0.5
pytest : 7.4.3
hypothesis : 6.88.3
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.17.2
pandas_datareader : None
bs4 : 4.12.2
bottleneck : None
dataframe-api-compat: None
fastparquet : None
fsspec : 2023.12.2
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 14.0.1
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None

[rhshadrach]

Thanks for the report, confirmed on main. Further investigation and PRs to fix are welcome!

[parthi-siva]

take

[dontgoto]

As mentioned in #58173, this issue extends beyond the Series constructor. Also Series.to_numpy() has the same issue (only apparent once one fixes the error described in the issue here).