APxx datasets giving false positives, even when -v 3-4 is given.

### Standard

CDISC SDTM/SDTMIG

### Reference Rule ID(s)

CORE-00376 CORE-000575 CORE-000701 CORE-000575 CORE-000852 CORE-000902

### Conformance Rule ID(s) (if published in CORE)

_No response_

### JIRA Ticket

_No response_

### CLI Command Used (if applicable)

python core.py -s SDTM -v 3.4 -d /path/to/datasets

### Rule YAML

```YAML
N/A
```

### Attach any sample test data file(s)

When working on an SDTMIG-3.4 submission for a customer that contains APMH (which is based on 3.2 I presume), we got a number of false positives for the above CORE rules.
Some of the rules even treat it as a "custom domain".
Essentially, as I gave -v 3-4, APMH should not have been evaluated at all, as it is based on 3.2, and also as it is a very old standard even breaking some of the principles of SDTM-1.4 on which SDTMIG-3.2 is based.

For users not realizing this, these false positives can be very confusing, even tempting them to "correct" their datasets.

My proposal is to, when an APxx dataset is in the list of datasets submitted to the engine, then these are excluded from the validation.
In the Excel tab "Dataset Details" , these could be marked as "Not evaluated".

I presume this is a just 1 or a few lines in the Python code.

### Attach any output report and/or log file(s)

N/A

### Expected output

See above

### Any Additional Information

_No response_