BUG: Expressions combining `.loc[]` and `.fillna()` causes inconsistencies with Pandas

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Reproducible Example

import os
import pandas as pd
os.environ["MODIN_ENGINE"] = "ray"
import modin.pandas as md
import numpy as np

pd_t1 = pd.DataFrame(
    {
        'c0': [1, np.nan],
        'c1': [np.nan ,True]
    }
)
md_t1 = md.DataFrame(
    {
        'c0': [1, np.nan],
        'c1': [np.nan ,True]
    }
)

print("Pandas:")
result = pd_t1.loc[lambda df: df['c1'].fillna(False)]
print(result)

print("Modin ray:")
result = md_t1.loc[lambda df: df['c1'].fillna(False)]
print(result)

Pandas:
   c0    c1
1 NaN  True

Modin ray:
    c0    c1
0  1.0   NaN
1  NaN  True

Issue Description

Expressions combining .loc[] and .fillna() can lead to inconsistencies between Modin and Pandas.
Both Modin's ray and dask engines may appear in the above situation.

Expected Behavior

Modin's results are the same with Pandas's.

Error Logs

Details

None

Installed Versions

Details

INSTALLED VERSIONS

commit : bce3707
python : 3.10.19
python-bits : 64
OS : Linux
OS-release : 6.14.0-35-generic
Version : #35~24.04.1-Ubuntu SMP PREEMPT_DYNAMIC Tue Oct 14 13:55:17 UTC 2
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

Modin dependencies

modin : 0.37.1
ray : 2.51.1
dask : 2025.11.0
distributed : 2025.11.0

pandas dependencies

pandas : 2.3.3
numpy : 1.26.4
pytz : 2025.2
dateutil : 2.9.0.post0
pip : 25.3
Cython : None
sphinx : None
IPython : 8.27.0
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.14.2
blosc : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : 2025.10.0
html5lib : None
hypothesis : None
gcsfs : None
jinja2 : 3.1.6
lxml.etree : None
matplotlib : 3.10.7
numba : 0.61.2
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
psycopg2 : None
pymysql : None
pyarrow : 22.0.0
pyreadstat : None
pytest : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : 1.15.3
sqlalchemy : 2.0.44
tables : None
tabulate : 0.9.0
xarray : 2025.6.1
xlrd : None
xlsxwriter : None
zstandard : 0.25.0
tzdata : 2025.2
qtpy : None
pyqt5 : None