Cross measures can be defined as the various techniques used to verify the accuracy of a measurement or calculation. The antonyms for cross measures could be imprecise, incorrect or inaccurate measurements. These antonyms indicate a lack of validity, reliability and trustworthiness in the data. Inaccurate measurements can lead to faulty conclusions and erroneous decisions. Hence, it is essential to use cross measures to ensure that the data is consistent and trustworthy. Other antonyms for cross measures could be subjective, biased, or flawed measurements which are often the result of human error, limited resources or inadequate equipment. Therefore, implementing cross measures will help to minimize these risks and improve the quality of data collected.