### 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)

"""Get the number of active dag runs for each dag."""
        query = session.query(cls.dag_id, func.count("*"))
        if dag_ids is not None:
            
            
            query = query.filter(cls.dag_id.in_(list(set(dag_ids))))
        if only_running:
            query = query.filter(cls.state == State.RUNNING)
        else:
            query = query.filter(cls.state.in_([State.RUNNING, State.QUEUED]))
        query = query.group_by(cls.dag_id)
        return {dag_id: count for dag_id, count in query.all()}
    @classmethod
    def next_dagruns_to_examine(
        cls,
        state: DagRunState,
        session: Session,
        max_number: int | None = None,
    ) -> list[DagRun]:
        """
        Return the next DagRuns that the scheduler should attempt to schedule.
        This will return zero or more DagRun rows that are row-level-locked with a "SELECT ... FOR UPDATE"
        query, you should ensure that any scheduling decisions are made in a single transaction -- as soon as
        the transaction is committed it will be unlocked.
        """
        from airflow.models.dag import DagModel
        if max_number is None:
            max_number = cls.DEFAULT_DAGRUNS_TO_EXAMINE
        
        query = (