Skill UI

This guide outlines the process for converting accepted academic papers into optional ACM reproducibility badges. It walks authors through the rigorous evaluation cycle, covering everything from initial opt-in before submission to providing detailed one-page artifact descriptions. The goal is to prove that the research results are available, functionally sound, highly reusable, and accurately reproducible by independent evaluators.

A comprehensive guide for authors submitting networking research to CoNEXT. It outlines best practices for achieving technical reproducibility, focusing on pinning traces, configurations, environments, and pipelines. Learn the critical timeline for optional ACM badging and how to maintain an honest data-availability posture for robust academic review.

A comprehensive guide for authors submitting to major AI conferences (like ECAI). It teaches the critical skill of separating core, decision-critical arguments (must be in the main body) from supporting details, proofs, and code (which belong in the optional supplement). This ensures reviewers can fairly judge the contribution despite strict page limits.

This guide details best practices for achieving reproducibility in highly theoretical computer science papers, such as those submitted to ICALP. Since artifact evaluation is absent, reproducibility hinges on the ability for any reader to independently verify every step of the proof. Key requirements include writing self-contained proofs, providing verifiable computational certificates, maintaining consistency between submissions, and optionally using formal verification tools like Coq or Lean.

A comprehensive guide for authors on how to package and present supplementary evidence for INTERSPEECH submissions. It clarifies the difference between core reviewed content and optional accompaniment (audio demos, extended analyses), emphasizing that the main paper must stand alone. Learn best practices for audio curation, layout, and navigating the 'three shelves' structure to maximize impact during the review process.

This comprehensive guide outlines the best practices for preparing a complete and reproducible research package for submission to the Journal of Banking & Finance (JBF) following Elsevier Option C guidelines. It details requirements for data availability statements, proper structuring of code and data access materials, and best methods for managing proprietary or restricted datasets (such as CRSP or Compustat), ensuring research transparency and verifiability.

This comprehensive guide provides a detailed preflight checklist for authors submitting manuscripts to the Journal of Business Venturing (JBV). It covers critical academic publishing requirements, including double-anonymization techniques (removing author identifiers, third-person self-citation), mandatory declarations (Competing Interest, CRediT, Generative-AI use), and adhering to Option C data availability policies. It ensures authors are fully prepared for the Elsevier Editorial Manager submission process.

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.

A comprehensive preflight checklist for submitting manuscripts to the Journal of Corporate Finance (JCF) via Editorial Manager. This guide verifies critical elements such as the non-refundable submission fee ($340), adherence to formatting rules (e.g., ≤250-word abstract, author-date citations), and inclusion of mandatory declarations (e.g., CoI, generative-AI disclosure, Option C data statement). Use this before finalizing your submission to ensure compliance and minimize desk rejection risks.

Provides comprehensive guidelines for authors submitting to the Journal of Economic Theory (JET). It details mandatory data sharing (Elsevier Option C), ensuring computational reproducibility for numerical examples, and proper declaration of generative AI usage. This playbook helps authors structure their submissions to meet high academic standards of verifiable evidence and transparency.

This guide assists authors in preparing research materials for submission to the Journal of Financial Intermediation (JFI), adhering to Elsevier Option C. It provides detailed instructions on managing, depositing, citing, and linking research data, code, and algorithms—whether the data is public, proprietary, or restricted (e.g., central bank registers). The goal is to ensure methodological rigor and reproducibility through the Data Statement.

This comprehensive guide provides a final preflight checklist for submitting manuscripts to academic journals like JFI via Editorial Manager. It covers mandatory components, including the submission fee, abstract word limits, keyword requirements, Generative AI declarations, and Option C data plans. It serves as a critical gatekeeping tool to ensure the manuscript meets all technical and procedural standards before final submission.