### Apache Airflow version

2.5.1

### What happened

I'd expect the `scheduler.tasks.running` metric to represent the number of running tasks, but it is always zero. It appears that #10956 broke this when it removed [the line that increments `num_tasks_in_executor`](https://github.com/apache/airflow/pull/10956/files#diff-bde85feb359b12bdd358aed4106ef4fccbd8fa9915e16b9abb7502912a1c1ab3L1363). Right now that variable is set to 0, never incremented, and the emitted as a gauge.

### What you think should happen instead

`scheduler.tasks.running` should either represent the number of tasks running or be removed altogether.

### How to reproduce

_No response_

### Operating System

Ubuntu 18.04

### Versions of Apache Airflow Providers

_No response_

### Deployment

Official Apache Airflow Helm Chart

### Deployment details

_No response_

### Anything else

_No response_

### Are you willing to submit PR?

- [X] 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)

query = (
                session.query(TI)
                .with_hint(TI, "USE INDEX (ti_state)", dialect_name="mysql")
                .join(TI.dag_run)
                .filter(DR.run_type != DagRunType.BACKFILL_JOB, DR.state == DagRunState.RUNNING)
                .join(TI.dag_model)
                .filter(not_(DM.is_paused))
                .filter(TI.state == TaskInstanceState.SCHEDULED)
                .options(selectinload("dag_model"))
                .order_by(-TI.priority_weight, DR.execution_date, TI.map_index)
            )
            if starved_pools:
                query = query.filter(not_(TI.pool.in_(starved_pools)))
            if starved_dags:
                query = query.filter(not_(TI.dag_id.in_(starved_dags)))
            if starved_tasks:
                task_filter = tuple_in_condition((TaskInstance.dag_id, TaskInstance.task_id), starved_tasks)
                query = query.filter(not_(task_filter))
            query = query.limit(max_tis)
            timer = Stats.timer("scheduler.critical_section_query_duration")
            timer.start()
            try:
                task_instances_to_examine: list[TI] = with_row_locks(
                    query,
                    of=TI,
                    session=session,
                    **skip_locked(session=session),
                ).all()
                timer.stop(send=True)