code: def df():
      mock_metadata = {
          "cord_uid": ["ej795nks", "", np.nan, "adygntbe", "adygntbe"],
          "doi": [
              "10.1289/ehp.7117",
              np.nan,
              "10.1371/journal.pmed.0030149",
              "",
              "10.1016/s0140-6736(03)13507-6",
          ],
          "title": [
              "Understanding the Spatial Clustering of",
              "The Application of the Haddon Matrix to",
              "Cynomolgus Macaque as an Animal Model for",
              "SARS: screening, disease associations",
              "SARS: screening, disease associations",
          ],
          "license": ["cc0", "cc0", "cc0", "no-cc", "els-covid"],
          "url": [
              "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11",
              "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12",
              "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13",
              "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7",
              "https://doi.org/10.1016/s0140-6736(03)13507-6",
          ],
      }
      return pd.DataFrame(mock_metadata)
  
file_path: recommenders/tests/data_validation/recommenders/datasets/test_covid_utils.py
imports: from unittest.mock import patch
  import pytest
  from recommenders.datasets.covid_utils import remove_duplicates, remove_nan, clean_dataframe, retrieve_text, get_public_domain_text
  import numpy
  import pandas
label_desc: Use image node_id 1 for calling a global function with example usage: df() and returns: pd