Abstract Screening Data Extraction is a systematic process in scholarly research synthesis that involves identifying and extracting relevant paper-level contributions—such as methods, models, frameworks, theories, constructs, datasets, tasks, or metrics—from academic abstracts through predefined eligibility criteria, distinguishing it from full-text screening by focusing exclusively on summary-level information to assess study relevance at an early stage of evidence selection.