Datasets:

HiTZ
/

saei-clinddx

# SAEI-CLINDDx validation

The `schema.json` file uses JSON Schema Draft 2020-12 and describes **one JSONL case record** (not an array). The files `data/es/test.jsonl` and `data/en/test.jsonl` share exactly the same fields and case IDs. Both languages remain **testing-only**.

## Run

```bash
python -m pip install 'jsonschema>=4.18'
python scripts/validate_dataset.py --report reports/validation_results.json
python scripts/validate_dataset.py --schema-only
python scripts/validate_dataset.py --expected-count 251
```

Exit code 0 means no errors; 1 means validation errors; 2 means the schema cannot be loaded. Warnings do not cause failure. JSON reports contain file path, JSONL line number, case ID, field, code, severity and message.

## Checks

- **JSON Schema:** required fields, string/integer types, valid language, ID pattern, core nonempty clinical text, no unknown keys.
- **Dataset integrity:** parse errors, blank JSONL lines, duplicate IDs, ID/year consistency, correct language directory, bilingual ID set equality, aligned year and author strings.
- **Content QA (default):** flags spreadsheet error strings such as `#ERROR!` in any clinical text as errors and empty differential-diagnosis fields as warnings. Content QA is a screening step, not full MQM evaluation or a clinical quality guarantee.

`summary`, `differential_diagnosis`, `authors`, and `discussion` permit empty strings to preserve missingness in the original dataset. These are **not** replaced with invented content. The optional `--expected-count` flag is deliberately absent by default so new cases can be added without editing the validator.

## Known status of current English version

The current English data contains 13 `#ERROR!` final-diagnosis values. These retain string type and therefore pass JSON Schema, but **fail content QA**. The files are intentionally left unchanged for traceability. Resolve those failures, then re-run the complete checks before release. No structural validator can guarantee accurate medical translation; use a separate human-adjudicated MQM evaluation.

	# SAEI-CLINDDx validation

	The `schema.json` file uses JSON Schema Draft 2020-12 and describes one JSONL case record (not an array). The files `data/es/test.jsonl` and `data/en/test.jsonl` share exactly the same fields and case IDs. Both languages remain testing-only.

	## Run

	```bash
	python -m pip install 'jsonschema>=4.18'
	python scripts/validate_dataset.py --report reports/validation_results.json
	python scripts/validate_dataset.py --schema-only
	python scripts/validate_dataset.py --expected-count 251
	```

	Exit code 0 means no errors; 1 means validation errors; 2 means the schema cannot be loaded. Warnings do not cause failure. JSON reports contain file path, JSONL line number, case ID, field, code, severity and message.

	## Checks

	- JSON Schema: required fields, string/integer types, valid language, ID pattern, core nonempty clinical text, no unknown keys.
	- Dataset integrity: parse errors, blank JSONL lines, duplicate IDs, ID/year consistency, correct language directory, bilingual ID set equality, aligned year and author strings.
	- Content QA (default): flags spreadsheet error strings such as `#ERROR!` in any clinical text as errors and empty differential-diagnosis fields as warnings. Content QA is a screening step, not full MQM evaluation or a clinical quality guarantee.

	`summary`, `differential_diagnosis`, `authors`, and `discussion` permit empty strings to preserve missingness in the original dataset. These are not replaced with invented content. The optional `--expected-count` flag is deliberately absent by default so new cases can be added without editing the validator.

	## Known status of current English version

	The current English data contains 13 `#ERROR!` final-diagnosis values. These retain string type and therefore pass JSON Schema, but fail content QA. The files are intentionally left unchanged for traceability. Resolve those failures, then re-run the complete checks before release. No structural validator can guarantee accurate medical translation; use a separate human-adjudicated MQM evaluation.