data-aware scheduling makes wrong dataset updates and downstream dag runs mapping when there are multiple updates during the execution of downstream dag

### Apache Airflow version 2.10.5 ### If "Other Airflow 2 version" selected, which one? _No response_ ### What happened? I created a demo procedure where the upstream dag updates the dataset continuously, while the downstream dag just sleep 30s to simulate some time-consume tasks. however, the dataset update and downstream dag run mappings are wired. it looks like below and there would be dangling dataset updates if I stop the upstream dag. the dangling dataset updates are actually processed by downstream dag but it showed in ui that it would never be processed. <img width="789" alt="Image" src="https://github.com/user-attachments/assets/fbe3f7c9-5e0a-48c2-b612-cd0747926e09" /> <img width="975" alt="Image" src="https://github.com/user-attachments/assets/ca8cf155-e2b6-4ae4-8049-cf2926f87a82" />  ### What you think should happen instead? <img width="973" alt="Image" src="https://github.com/user-attachments/assets/046e073a-8023-4ec9-9d5a-345019799068" /> ### How to reproduce ``` from datetime import datetime as datetime import airflow from airflow import DAG from airflow.operators.dummy_operator import DummyOperator from airflow.operators.trigger_dagrun import TriggerDagRunOperator from airflow.operators.python import PythonOperator from airflow.operators.bash_operator import BashOperator from airflow.datasets import Dataset dataset1 = Dataset('s3://folder1/dataset_2.txt') with DAG( dag_id="upstream_dag_A", start_date=datetime(2023, 1, 1), catchup=False, schedule="@continuous", max_active_runs=1, ) as dag: start_task = BashOperator( task_id="start_task", bash_command="echo 'Start task'", outlets=[dataset1], ) with DAG( "downstream-dataset-dag", start_date=datetime(2023, 1, 1), schedule=[dataset1], catchup=False, max_active_runs=1, ) as dag: start_task = BashOperator( task_id="start_task", # bash_command="echo 'Start task'", bash_co…