Final answer:
In presenting an audit report, a researcher would de-bias the results to ensure unbiased conclusions, which is distinct from preventing a model from launching, scoring the input attributes, or re-training the model.
Step-by-step explanation:
In presenting an audit report, a researcher would de-bias the results. This process includes assessing and adjusting the data or model to reduce bias, ensuring that the conclusions of the audit are based on fair, accurate, and unbiased information. This practice is crucial in fields like economics where audit studies are used to detect discrimination in various sectors such as education, housing, the labor market, and the criminal justice system. The goal of de-biasing is to improve the validity and reliability of the study's outcomes, rather than the options of preventing a model from launching, scoring the weight of input attributes on output, or re-training the model.
Differentiating between options, preventing a model from launching would be more relevant if the audit report revealed a critical flaw that could not be remedied. Scoring the weight of input attributes on output refers to determining the importance of different input factors in the model's decision-making process, which might be a part of model evaluation but is not specific to the presentation of an audit report. Lastly, re-training the model might be a step taken if the audit reveals significant issues with the model's performance, but this too is outside the scope of merely presenting an audit report.