[BUG] Creating a task requires an estimation procedure ID, but procedure is not correctly created

The issue is in openml/tasks/task.py, specifically the create_task() function and the OpenMLTask class handling of estimation_procedure_id. Start by examining the default value flow and where the procedure becomes None. Test with the provided script on a local docker instance to reproduce the error. Check the split dimensions and estimation procedure attributes after task creation to confirm the bug.

It is important to first note that the tasks/task.py appears to be slightly different from the version obtainable through pip install "openml==0.15.1", which would've elevated the priority while reducing the effort had the GitHub version not experienced the same bug.

The create_task() function requires an estimation_procedure_id parameter despite it having a default value in all cases, which all funnel towards the same OpenMLTask class where the handling of estimation procedure appears to break*.
It was tested without publication on the main server, as well as with publication on a local docker instance (test server does not have any procedures), where in both cases the create_task() function creates a task with Estimation Procedure equal to None and no data split (errors follow).

import openml
from openml.tasks import TaskType

openml.config.server = "..."
openml.config.apikey = "..."

did = 128  # iris

try:
    my_task = openml.tasks.create_task(
        task_type=TaskType.SUPERVISED_CLASSIFICATION,
        dataset_id=did,
        target_name="class",
        evaluation_measure="predictive_accuracy",
        estimation_procedure_id=1,
    )
    my_task.publish()
except openml.exceptions.OpenMLServerException as e:
    # Error code for 'task already exists'
    if e.code == 614:
        # Lookup task
        tasks = openml.tasks.list_tasks(data_id=did, output_format='dataframe')
        tasks = tasks.query(
            'task_type == "Supervised Classification" '
            'and estimation_procedure == "10-fold Crossvalidation" '
            'and evaluation_measures == "predictive_accuracy"'
        )
        display(tasks)
        task_id = tasks.loc[:, "tid"].values[0]
        print("Task already exists. Task ID is", task_id)
    
print(my_task)
print(my_task.estimation_procedure)
print(my_task.get_split_dimensions())

* Unconfirmed, however it is a good starting point.