### Apache Airflow version

2.7.0

### What happened

Relates to investigation of #30327

When you define a DAG with a `schedule=datetime.timedelta(days=1)` and `catchup=False` and you manually trigger a run in the past (logical date in the past, e.g. a few days ago) then upon completion of the run another scheduled run is triggered - irrespective of a previous scheduled run was made just before (not a day ago)

### What you think should happen instead

A manual run should not trigger another run as the scheduling in general should follow the delta time definition of the DAG.

### How to reproduce

Use the following example DAG code and enable scheduling:
```
with DAG(
    dag_id="after_workday_delta_regression",
    start_date=pendulum.datetime(2023, 8, 1, tz="UTC"),
    catchup=False,
    schedule=datetime.timedelta(days=1),
    params={"test": 123}
):
    @task
    def test(ti: TaskInstance=None):
        print(ti.execution_date)
    test()
```

Wait a moment and see that one schedule is run automatically.
Then trigger a manual DAG run and set the execution date/logical date a few days into the past.
After execution you see a third run of the DAG just at the time of completion of the manual trigger as execution date. But the first execution was just a few moments before, not respecting the desired delta of 1 day.

### Operating System

Ubuntu 20.04 / Breeze Dev setup in Py 3.8 Container

### Versions of Apache Airflow Providers

not relevant

### Deployment

Other

### Deployment details

Started and tested with latest main branch and breeze.

### Anything else

I tried to find the root cause but was not able to locate it. Suspect it is rooted in scheduler_job_runner.py.
I'd supply a fix but was not able to fund the root cause. Expert knowledge is needed probably.

### 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)

if state in (DagRunState.SUCCESS, DagRunState.FAILED):
                
                job_runner.num_runs = 1
            orig_set_state(self, state, **kwargs)  
        def watch_heartbeat(*args, **kwargs):
            if len(num_queued_tis) < 3 or len(num_finished_events) < 3:
                return
            queued_any_tis = any(val > 0 for val in num_queued_tis)
            finished_any_events = any(val > 0 for val in num_finished_events)
            assert (
                queued_any_tis or finished_any_events
            ), "Scheduler has stalled without setting the DagRun state!"
        set_state_spy = mock.patch.object(DagRun, "set_state", new=watch_set_state)
        heartbeat_spy = mock.patch.object(job_runner, "heartbeat", new=watch_heartbeat)
        with heartbeat_spy, set_state_spy, do_scheduling_spy, executor_events_spy:
            run_job(job_runner.job, execute_callable=job_runner._execute)
    @pytest.mark.long_running
    @pytest.mark.parametrize("dag_id", ["test_mapped_classic", "test_mapped_taskflow"])
    def test_mapped_dag(self, dag_id, session):