### Description of the issue/feature this PR addresses: 
**Issue:** A recent update to support `certificateFingerprint` introduced a regression for existing users authenticating with standard certificates (AKA `certificateSubject`). Because the matching logic strictly checked for the company NIP within the certificate subject, it failed for users using personal PESEL certificates to act on a company's behalf. 

**Previous PR:** https://github.com/odoo/odoo/pull/264851 

**Solution:** Expanded the string-matching heuristic in the XML signer to strip formatting characters from the NIP and explicitly checks for standard Polish qualified certificate prefixes (VATPL and PNOPL) to accurately get the identifier type.

### Current behavior before PR: 
When a user logs in via a personal PESEL certificate for a company context, the NIP check fails and miscategorizes the payload as a `certificateFingerprint`. KSeF rejects this mismatch, causing a 400 error for previously working setups.

### Desired behavior after PR is merged: 
The authentication flow distinguishes between `certificateSubject` and `certificateFingerprint` by checking for valid Polish prefixes or exact cleaned NIP matches. Existing customers are restored to working order natively, and new customers using manual fingerprints are still supported without requiring any database or UI changes.

opw-6251153

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Forward-Port-Of: odoo/odoo#267060

### Description of the issue/feature this PR addresses:
Prevent Out of Memory (OOM) crashes and drastically improve execution speed when generating the Swedish SIE4 verification export for massive datasets.

### Current behavior before PR:
When exporting a large volume of journal entries (e.g., 190,000+ account moves), the `_export_l10n_se_sie4_verification` method relies on iterating through heavy ORM recordsets and accessing relational child fields (move.line_ids) inside a loop. This triggers a severe N+1 query problem, maxing out server RAM and causing an OOM crash.

### Desired behavior after PR is merged:
The method now utilizes a hybrid data extraction approach:
- The ORM is used strictly to safely evaluate domains (multi-company rules, dates, states) and fetch a lightweight list of valid move_ids.
- A single SQL query with JOIN statements fetches all parent moves, child lines, and account codes in exactly one database query.
- itertools.groupby chunks the flat, lightweight dictionary results back into their respective journal entries.
The export now handles massive datasets in seconds with minimal memory overhead, while remaining perfectly secure.

### Benchmark:

For Memory:
| # Input Data | Before PR | After PR |
| -------- | -------- | -------- |
| ~190,000 moves | MemoryError | 407MB|
| ~200,000 moves | 1.8GB | 174.8 MB|

For Speed:
| # Input Data | Before PR | After PR |
| -------- | -------- | -------- |
| ~190,000 moves | MemoryError | 5.10s |
| ~200,000 moves | 1m29s| 5.3s|

### Reference:
opw-6067999

Forward-Port-Of: odoo/enterprise#117577
Forward-Port-Of: odoo/enterprise#113227