### 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)

Stats.incr(
                    "scheduler.tasks.killed_externally",
                    tags={"dag_id": ti.dag_id, "task_id": ti.task_id},
                )
                msg = (
                    "Executor reports task instance %s finished (%s) although the "
                    "task says it's %s. (Info: %s) Was the task killed externally?"
                )
                self.log.error(msg, ti, state, ti.state, info)
                
                try:
                    dag = self.dagbag.get_dag(ti.dag_id)
                    task = dag.get_task(ti.task_id)
                except Exception:
                    self.log.exception("Marking task instance %s as %s", ti, state)
                    ti.set_state(state)
                    continue
                ti.task = task
                if task.on_retry_callback or task.on_failure_callback:
                    request = TaskCallbackRequest(
                        full_filepath=ti.dag_model.fileloc,
                        simple_task_instance=SimpleTaskInstance.from_ti(ti),
                        msg=msg % (ti, state, ti.state, info),
                        processor_subdir=ti.dag_model.processor_subdir,
                    )
                    self.job.executor.send_callback(request)
                else:
                    ti.handle_failure(error=msg % (ti, state, ti.state, info), session=session)
        return len(event_buffer)
    def _execute(self) -> int | None: