Skill UI

Provides detailed guidelines for authors submitting manuscripts to academic journals, specifically addressing the strict limit of 10 tables and figure panels, along with a 10-page supplementary cap. This guide teaches authors how to critically select, consolidate, and present key research results—such as marginal effects, event studies, or decomposition plots—to ensure every exhibit is self-contained, highly clear, and robust enough to pass expert review.

This guide outlines the strict writing and formatting requirements for submitting scholarly manuscripts to a general social science audience. Key guidelines include adopting the Chicago Manual of Style (17th ed., author-date), maintaining an accessible, argument-first prose, and adhering to a stringent total word count cap that includes all references. It ensures academic submissions are professional, readable, and properly formatted for publication.

This skill provides comprehensive guidance for authors submitting highly rigorous theoretical computer science manuscripts to top-tier venues like SIAM Journal on Computing (SICOMP). It covers required standards for algorithmic design, computational complexity, formal proofs, house style, and the high bar for theoretical contribution necessary for foundational academic publishing.

A comprehensive guide for submitting networking research artifacts for SIGCOMM conferences. It dictates how to package code, downscale topologies, substitute traces, and pin environments so that reviewers can independently verify and reproduce the paper's headline results, establishing verifiable scientific claims.

This comprehensive guide outlines the structured process for authors responding to peer review feedback for top-tier academic conferences (e.g., SIGCOMM). It critically distinguishes between drafting a concise, decision-focused rebuttal and executing a formal, contract-bound one-shot revision. It provides strict guidelines on building the required submission packet, including point-by-point responses, change-marked manuscripts, and evidence anchoring, ensuring submissions meet high academic standards.

Provides comprehensive guidelines for improving the reproducibility of academic network measurements and research artifacts, particularly for conferences like SIGCOMM. It details the necessary evidence map and the 'four ledgers'—topology, traffic, configuration, and run—to ensure that all reported claims can be accurately recreated and verified by the wider academic community.

A comprehensive guide for ensuring the reproducibility of Information Retrieval (IR) research, essential for SIGIR submissions. It details best practices for pinning data collection versions, index settings, neural model hyperparameters, and managing non-determinism. It helps researchers document artifacts—not just promises—to validate reported gains.

Provides comprehensive guidelines for achieving high levels of scientific reproducibility for academic papers, particularly those in systems metrics. It covers mapping claims to verifiable evidence, ensuring simulators are seeded and deterministic, and documenting measurement provenance to allow reviewers to independently verify all reported results.

Provides strict guidelines for structuring and partitioning academic papers submitted to SIGMETRICS. It details the proper placement of content, specifying what must reside in the main body (decision-critical claims like theorems and assumptions), what belongs in the appendices (full proofs, extended analysis), and what constitutes the anonymized artifact. Adherence ensures the core argument is reviewable solely from the primary reviewed pages.

A comprehensive guide for authors preparing methodological papers for submission to SMR. It outlines strict standards for creating a usable, reproducible package, including structured code, master scripts with fixed seeds, and formal data/code availability statements, ensuring the method can be run by others.

Provides expert guidelines for creating high-rigor methodological exhibits for the Sociological Methods & Research (SMR) journal. Focuses on constructing self-contained simulation grids, method-comparison tables, and diagnostic figures that clearly communicate methodological arguments, ensuring reviewers can audit claims directly without relying on surrounding prose.

This guide outlines the best practices for preparing system artifacts for academic evaluation, following the ACM Artifact Review and Badging scheme. It details how authors must ensure reproducibility, especially for tail latency and cost results, by providing scaled-down testbeds, comprehensive documentation, and clear provenance tracking to satisfy conference evaluators.