### 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)

run_id=dag_run.run_id,
                is_failure_callback=True,
                processor_subdir=dag_model.processor_subdir,
                msg="timed_out",
            )
            dag_run.notify_dagrun_state_changed()
            duration = dag_run.end_date - dag_run.start_date
            Stats.timing(f"dagrun.duration.failed.{dag_run.dag_id}", duration)
            Stats.timing("dagrun.duration.failed", duration, tags={"dag_id": dag_run.dag_id})
            return callback_to_execute
        if dag_run.execution_date > timezone.utcnow() and not dag.allow_future_exec_dates:
            self.log.error("Execution date is in future: %s", dag_run.execution_date)
            return callback
        if not self._verify_integrity_if_dag_changed(dag_run=dag_run, session=session):
            self.log.warning("The DAG disappeared before verifying integrity: %s. Skipping.", dag_run.dag_id)
            return callback
        
        schedulable_tis, callback_to_run = dag_run.update_state(session=session, execute_callbacks=False)
        
        if dag_run.state in State.finished_dr_states:
            
            if self._should_update_dag_next_dagruns(dag, dag_model, session=session):
                dag_model.calculate_dagrun_date_fields(dag, dag.get_run_data_interval(dag_run))
        
        
        
        
        dag_run.schedule_tis(schedulable_tis, session, max_tis_per_query=self.job.max_tis_per_query)
        return callback_to_run
    def _verify_integrity_if_dag_changed(self, dag_run: DagRun, session: Session) -> bool: