CLI isn't overriding settings in the baseline.toml file

Nobody has claimed this yet.

Training jobs are still calculating means even though they are set to False in the CLI.

CLI Command:

```
uv run python -m saev train
--sweep configs/preprint/baseline.toml
--data.shard-root /fs/scratch/PAS2136/oh-scipe/activations/406094ac63e6de7a592d5ddbaa581e147d51a2596e39732dafe2171cfe15225b
--data.layer -1
--data.patches patches
--data.scale-mean False
--data.scale-norm False sae:relu
--sae.d-vit 768
```
baseline.toml file contents:
```
tag = "baseline-v4.8"

lr = [3e-4, 1e-3, 3e-3]

n_lr_warmup = 500
n_sparsity_warmup = 500

[sae]
normalize_w_dec = true
remove_parallel_grads = true
exp_factor = [16, 32]

[objective]
sparsity_coeff = [4e-4, 8e-4, 1.6e-3]

[data]
scale_mean = true
scale_norm = true
```

An example of this working correctly is in the python formatter 'black' where default options can be overridden in the CLI:
https://github.com/psf/black/blob/main/pyproject.toml

Reproduce the issue with `uv run python -m saev train` and the options shown, using `configs/preprint/baseline.toml` as the configuration input. Trace how the `data.scale_mean` and `data.scale_norm` values are parsed and overridden; done means the CLI values `False` take precedence over the TOML defaults during training.

Written by the indexing model from the issue text.