Skill UI

This guide provides a comprehensive checklist and systematic approach for enhancing the reproducibility of research in Computer Graphics and CAD. It addresses the inherent sensitivity of graphics and geometry results to environment variables, random seeds, rendering parameters, and data versions, ensuring that published results can be reliably replicated by reviewers and readers.

This guide helps researchers properly structure graphical and CAD papers submitted to academic journals. It details the separation of core, 'decisive' evidence (main results, key figures) that must reside in the main text, versus 'extensive' supplementary materials (videos, extra data, full derivations). It emphasizes maintaining the self-sufficiency of the main article while ensuring all necessary evidence is presented.

This guide assists researchers in validating if their proposed topic aligns with the scope of the Journal of Computer-Aided Design & Computer Graphics (JCAD&CG). It systematically checks the core contribution, focusing on graphics, geometry, visualization, VR/AR, and CAD/CAE techniques, helping authors ensure sufficient technical increment and preventing rejection due to scope mismatch.

This guide provides a comprehensive checklist and style manual for authors submitting papers to the Journal of Computer-Aided Design & Computer Graphics (JCAD&CG). It covers all necessary formatting details, including the four elements of a reportative abstract, the problem-gap-contribution structure, adherence to GB/T 7714 citation standards, and specific rules for graphical evidence presentation in CAD and graphics research.

This guide helps authors sharpen the stated contribution of an academic manuscript, particularly in corporate finance. It instructs users on how to transform research findings into a crisp, compelling claim that clearly states 'what is new and why it matters.' It is essential for drafting abstracts, introductions, and cover letters to maximize the chance of passing an editor's initial screening.

A comprehensive guide for designing and defending the causal identification strategy in empirical corporate finance research. It covers advanced methods such as Staggered DID, Instrumental Variables (IV), Regression Discontinuity Design (RDD), and Event Studies, providing checklists to address crucial econometric threats like endogeneity, selection bias, and reverse causality for high-impact publications.

A comprehensive guide for academic authors on how to precisely position their research within the specialized field of corporate finance. It teaches how to identify the specific theoretical 'strand' (e.g., capital structure, governance, M&A) and articulate a clear, marginal contribution by contrasting the work against 2-3 closest existing papers, thereby transforming vague claims into rigorous academic arguments.

A comprehensive guide for authors submitting to the Journal of Corporate Finance (JCF). It details how to comply with Elsevier's Option C data availability requirements, focusing on drafting the data availability statement and structuring the research archive. It provides best practices for handling licensed, proprietary data (e.g., Compustat, CRSP) by recommending the sharing of construction code and access instructions, rather than raw data deposits.

This guide provides a comprehensive strategic overview of the peer-review process for top-tier academic finance journals, such as JCF. It details expectations regarding single-blind review, the impact of active desk rejection policies, mandatory declarations (AI, conflict of interest), and provides actionable strategies for interpreting decision letters (R&R, desk reject). It is designed to help researchers plan manuscript framing and revision efforts for maximum success.

A comprehensive guide detailing the conventions for constructing high-quality empirical tables and figures, especially for corporate finance and econometrics journals. Covers best practices for reporting summary statistics, fixed effects, clustering, event-study/CAR plots, and ensuring self-contained notes for academic publication.

This guide helps researchers assess if a corporate finance question is suitable for the Journal of Corporate Finance (JCF). It provides a framework to determine if the topic fits the journal's empirical or theoretical remit (e.g., governance, M&A, financial structure) and advises on the optimal article format (full-length vs. shorter paper). It serves as a critical self-check against common academic rejection pitfalls.

This skill guides researchers in refining their manuscript's core contribution for top academic journals like JCP. It teaches how to shift the narrative focus from simply reporting an 'effect' (X increases Y) to articulating the underlying psychological 'PROCESS' or 'mechanism' (X increases Y *because* it changes M). It ensures claims are theoretically surprising, scope-bound, and relevant to consumer behavior.