code: def annotate_hl_result_table_linear(result_table):
      result_table = result_table.annotate(
          z_results=hl.zip(
              result_table["phenotypes"],
              result_table["p_value"],
              result_table["beta"],
              result_table["y_transpose_x"],
              result_table["standard_error"],
          )
      )
  
      result_table = result_table.explode("z_results")
  
      result_table = result_table.annotate(
          phenotype=result_table["z_results"][0],
          n=result_table["n"],
          sum_x=result_table["sum_x"],
          p_value=result_table["z_results"][1],
          beta=result_table["z_results"][2],
          y_transpose_x=result_table["z_results"][3],
          standard_error=result_table["z_results"][4],
      ).drop("z_results")
  
      return result_table
  
label_desc: Use image node_id 1 for calling a global function with example usage: annotate_hl_result_table_linear(result_table) and returns: result_table