### What do you see as an issue?

The [/dags/{dag_id}/details](https://airflow.apache.org/docs/apache-airflow/stable/stable-rest-api-ref.html#operation/post_set_task_instances_state) endpoint of the REST API does not return all of the keys that are listed in the documentation. If I run `curl -X GET localhost:8080/api/v1/dags/{my_dag}/details`, then compare the results with the results in the documentation, you can see the following missing keys:

```python
>>> for key in docs.keys():
...     if not key in actual.keys():
...             print(key)
...
root_dag_id
last_parsed_time
last_pickled
last_expired
scheduler_lock
timetable_description
has_task_concurrency_limits
has_import_errors
next_dagrun
next_dagrun_data_interval_start
next_dagrun_data_interval_end
next_dagrun_create_after
template_search_path
```

### Solving the problem

Either remove these keys from the documentation or fix the API endpoint

### Anything else

_No response_

### Are you willing to submit PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

outlet_references[(task.dag_id, task.task_id)].add(d.uri)
                    outlet_datasets[DatasetModel.from_public(d)] = None
        all_datasets = outlet_datasets
        all_datasets.update(input_datasets)
        
        stored_datasets: dict[str, DatasetModel] = {}
        new_datasets: list[DatasetModel] = []
        for dataset in all_datasets:
            stored_dataset = session.scalar(
                select(DatasetModel).where(DatasetModel.uri == dataset.uri).limit(1)
            )
            if stored_dataset:
                
                
                
                stored_dataset.is_orphaned = expression.false()
                stored_datasets[stored_dataset.uri] = stored_dataset
            else:
                new_datasets.append(dataset)
        dataset_manager.create_datasets(dataset_models=new_datasets, session=session)
        stored_datasets.update({dataset.uri: dataset for dataset in new_datasets})
        del new_datasets
        del all_datasets
        
        for dag_id, uri_list in dag_references.items():
            dag_refs_needed = {
                DagScheduleDatasetReference(dataset_id=stored_datasets[uri].id, dag_id=dag_id)
                for uri in uri_list
            }
            dag_refs_stored = set(