### Apache Airflow version

2.4.3

### What happened

A significant fraction of the DAG Runs of a DAG that has 2+ consecutive mapped tasks which are are being passed an empty list are marked as failed when all tasks are either succeeding or being skipped. This was supposedly fixed with issue #25200 but the problem still persists.
![image](https://user-images.githubusercontent.com/46539900/203193331-db94c793-36e8-4fbd-bc45-29865c44fbfc.png)

### What you think should happen instead

The DAG Run should be marked success.

### How to reproduce

The real world version of this DAG has several mapped tasks that all point to the same list, and that list is frequently empty. I have made a minimal reproducible example.

```
from datetime import datetime

from airflow import DAG
from airflow.decorators import task


with DAG(dag_id="break_mapping", start_date=datetime(2022, 3, 4)) as dag:

    @task
    def add_one(x: int):
        return x + 1

    @task
    def say_hi():
        print("Hi")

    @task
    def say_bye():
        print("Bye")

    added_values = add_one.expand(x=[])
    added_more_values = add_one.expand(x=[])
    added_more_more_values = add_one.expand(x=[])
    say_hi() >> say_bye() >> added_values
    added_values >> added_more_values >> added_more_more_values
```

### Operating System

Debian Bullseye

### Versions of Apache Airflow Providers

_No response_

### Deployment

Astronomer

### Deployment details

_No response_

### 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)

"""
        Check that "next_dagruns_to_examine" ignores runs from paused/inactive DAGs
        and gets running/queued dagruns
        """
        dag = DAG(dag_id="test_dags", start_date=DEFAULT_DATE)
        EmptyOperator(task_id="dummy", dag=dag, owner="airflow")
        orm_dag = DagModel(
            dag_id=dag.dag_id,
            has_task_concurrency_limits=False,
            next_dagrun=DEFAULT_DATE,
            next_dagrun_create_after=DEFAULT_DATE + datetime.timedelta(days=1),
            is_active=True,
        )
        session.add(orm_dag)
        session.flush()
        dr = dag.create_dagrun(
            run_type=DagRunType.SCHEDULED,
            state=state,
            execution_date=DEFAULT_DATE,
            data_interval=dag.infer_automated_data_interval(DEFAULT_DATE),
            start_date=DEFAULT_DATE if state == DagRunState.RUNNING else None,
            session=session,