### 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)

tis_to_adopt_or_reset = with_row_locks(
                        query, of=TI, session=session, **skip_locked(session=session)
                    )
                    tis_to_adopt_or_reset = session.scalars(tis_to_adopt_or_reset).all()
                    to_reset = self.job.executor.try_adopt_task_instances(tis_to_adopt_or_reset)
                    reset_tis_message = []
                    for ti in to_reset:
                        reset_tis_message.append(repr(ti))
                        ti.state = None
                        ti.queued_by_job_id = None
                    for ti in set(tis_to_adopt_or_reset) - set(to_reset):
                        ti.queued_by_job_id = self.job.id
                    Stats.incr("scheduler.orphaned_tasks.cleared", len(to_reset))
                    Stats.incr("scheduler.orphaned_tasks.adopted", len(tis_to_adopt_or_reset) - len(to_reset))
                    if to_reset:
                        task_instance_str = "\n\t".join(reset_tis_message)
                        self.log.info(
                            "Reset the following %s orphaned TaskInstances:\n\t%s",
                            len(to_reset),
                            task_instance_str,
                        )
                    
                    
                    session.flush()
                except OperationalError:
                    session.rollback()
                    raise
        return len(to_reset)
    @provide_session
    def check_trigger_timeouts(self, session: Session = NEW_SESSION) -> None: