def METHOD_NAME(self, lab, embeddings):
    issue_manager = OutlierIssueManager(datalab=lab, k=3, threshold=0.66666)
    issue_manager.find_issues(features=embeddings["embedding"])
    issues, summary, info = issue_manager.issues, issue_manager.summary, issue_manager.info
    expected_issue_mask = np.array([False] * 4 + [True])
    assert np.all(
        issues["is_outlier_issue"] == expected_issue_mask
    ), "Issue mask should be correct"
    assert summary["issue_type"][0] == "outlier"
    assert summary["score"][0] == pytest.approx(expected=0.7732146, abs=1e-7)
    assert issue_manager.threshold == 0.66666