### 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)

self.processor_agent.end()
                except Exception:
                    self.log.exception("Exception when executing DagFileProcessorAgent.end")
            self.log.info("Exited execute loop")
        return None
    @provide_session
    def _update_dag_run_state_for_paused_dags(self, session: Session = NEW_SESSION) -> None:
        try:
            paused_runs = session.scalars(
                select(DagRun)
                .join(DagRun.dag_model)
                .join(TI)
                .where(
                    DagModel.is_paused == expression.true(),
                    DagRun.state == DagRunState.RUNNING,
                    DagRun.run_type != DagRunType.BACKFILL_JOB,
                )
                .having(DagRun.last_scheduling_decision <= func.max(TI.updated_at))
                .group_by(DagRun)
            )
            for dag_run in paused_runs:
                dag = self.dagbag.get_dag(dag_run.dag_id, session=session)
                if dag is not None:
                    dag_run.dag = dag
                    _, callback_to_run = dag_run.update_state(execute_callbacks=False, session=session)
                    if callback_to_run:
                        self._send_dag_callbacks_to_processor(dag, callback_to_run)
        except Exception as e:  
            self.log.exception("Failed to update dag run state for paused dags due to %s", e)
    def _run_scheduler_loop(self) -> None: