Skill UI

A comprehensive guide for authors preparing accepted academic papers for publication in the ACM Digital Library. This process covers de-anonymization (restoring author details, funding, and public links), applying the strict double-column format, adhering to page budgets, incorporating all results promised during the rebuttal, and finalizing necessary metadata and conference artifacts.

This guide details the critical process of transforming an accepted, anonymous conference paper into its final, published, open-access version for the ACL Anthology. It covers the essential 'three-source merge' process: integrating reviewer-promised revisions, restoring author identity and community acknowledgements, correcting metadata, and managing conference logistics. Essential reading for authors submitting to top-tier NLP venues like NAACL.

A comprehensive checklist for confirming clinical ethics and research integrity required for academic submissions, adhering to standards set by the Declaration of Helsinki and ICMJE guidelines. It guides authors on securing IRB approval, obtaining informed consent, managing conflicts of interest, defining authorship roles, and ensuring data transparency through mandatory data-sharing statements. Essential for preparing manuscripts for high-impact medical journals.

This guide directs authors on how to structure the related work section for academic papers in database theory (e.g., for venues like PODS, ICDT). It emphasizes a 'delta-first' approach, requiring authors to compare their specific *results* (theorems, bounds, dichotomies) directly against the nearest prior *results*, rather than simply cataloging related citations. It also covers complex rules regarding self-citation, anonymity, and overlap declaration with concurrent or prior-version work.

This guide details the strict requirements for data transparency and reproducibility when submitting manuscripts to the Population and Development Review (PDR). It covers creating data availability statements, depositing materials in FAIR repositories, documenting code with versions, and managing restricted data access, ensuring adherence to modern research integrity standards.

A comprehensive guide for academic authors adopting open science standards, based on TOP Guidelines. It outlines best practices for ensuring research reproducibility, covering data citation, data provenance documentation, data sharing via repositories (Dataverse/QDR), and managing restricted-data paths for various evidence types.

This guide outlines the comprehensive steps required to convert an accepted, anonymous academic paper into its final, published 'camera-ready' version for major conferences (e.g., RecSys). It covers crucial tasks such as restoring author details, affiliations, funding, integrating rebuttal promises, ensuring proper ACM two-column reflow, and managing public code/data repository release.

This guide outlines the comprehensive policy and architecture required for submitting a fully reproducible replication package to The Review of Economics and Statistics (REStat). It details how to structure the repository, including data, master scripts, and the README file, ensuring that every result can be traced and regenerated by other researchers.

A comprehensive preflight checklist designed for authors submitting academic manuscripts to specialized journals. It guides users through verifying complex requirements, including formatting rules (double-spacing, font size), style compliance, data availability policies, and submission fee procedures, ensuring the paper is submission-ready and meets journal standards.

This guide details how to assemble a submission-ready replication package for top academic journals, such as The Review of Economic Studies (REStud). It covers the necessary repository structure, mandatory README sections, and coding best practices (e.g., master scripts, relative paths, version pinning) to ensure that the data and code can be fully reproduced and verified by journal editors before publication.

A comprehensive guide for authors submitting manuscripts to the RAND Journal of Economics (RJE). It details how to build a robust, reproducible replication package, focusing on creating a master script, pinning the computational environment, and properly documenting restricted datasets. It specifically addresses RJE's unique policy, which does not mandate formal data or code deposits, while ensuring academic rigor is maintained for reviewers.

Provides comprehensive guidelines for authors preparing manuscripts for high-level academic publication, focusing specifically on data availability and transparency. It guides users through drafting the required data availability statement, depositing data and code in public repositories (e.g., OSF, Zenodo), and methods for documenting restricted or qualitative sources to ensure maximum reproducibility and ethical compliance.