.struct.field() after shuffle() seems to produce incorrect results

[cmdlineluser]

Checks

• I have checked that this issue has not already been reported.
• I have confirmed this bug exists on the latest version of Polars.

Reproducible example

import polars as pl

df = pl.DataFrame({"a": [1, 2, 3], "b": [1, 2, 3]})

Log output

No response

Issue description

Noticed while experimenting with #18233

Using a struct should keep each "row" intact when shuffling:

df.select(pl.struct(pl.all()).shuffle())
# shape: (3, 1)
# ┌───────────┐
# │ a         │
# │ ---       │
# │ struct[2] │
# ╞═══════════╡
# │ {3,3}     │
# │ {1,1}     │
# │ {2,2}     │
# └───────────┘

Adding field extraction seems to break this:

df.select(pl.struct(pl.all()).shuffle().struct.field("*"))
# shape: (3, 2)
# ┌─────┬─────┐
# │ a   ┆ b   │
# │ --- ┆ --- │
# │ i64 ┆ i64 │
# ╞═════╪═════╡
# │ 1   ┆ 3   │
# │ 2   ┆ 2   │
# │ 3   ┆ 1   │
# └─────┴─────┘

It should be equivalent to unnest in this case?

df.select(pl.struct(pl.all()).shuffle()).unnest("a")
# shape: (3, 2)
# ┌─────┬─────┐
# │ a   ┆ b   │
# │ --- ┆ --- │
# │ i64 ┆ i64 │
# ╞═════╪═════╡
# │ 2   ┆ 2   │
# │ 3   ┆ 3   │
# │ 1   ┆ 1   │
# └─────┴─────┘

Expected behavior

field extraction and unnest should produce the same result?

Installed versions

--------Version info---------
Polars:               1.5.0
Index type:           UInt32
Platform:             macOS-13.6.1-arm64-arm-64bit
Python:               3.12.2 (main, Feb  6 2024, 20:19:44) [Clang 15.0.0 (clang-1500.1.0.2.5)]

----Optional dependencies----
adbc_driver_manager:  <not installed>
cloudpickle:          <not installed>
connectorx:           <not installed>
deltalake:            <not installed>
fastexcel:            <not installed>
fsspec:               <not installed>
gevent:               <not installed>
great_tables:         <not installed>
hvplot:               <not installed>
matplotlib:           <not installed>
nest_asyncio:         <not installed>
numpy:                1.26.4
openpyxl:             <not installed>
pandas:               2.2.1
pyarrow:              15.0.2
pydantic:             <not installed>
pyiceberg:            <not installed>
sqlalchemy:           <not installed>
torch:                <not installed>
xlsx2csv:             <not installed>
xlsxwriter:           <not installed>