Skill UI

A comprehensive skill designed to assess the suitability of a manuscript for The BMJ (British Medical Journal). It provides expert guidance on journal positioning, required methodological rigor (e.g., CONSORT, PRISMA, STROBE compliance), open data commitments, structured abstract requirements, and the specific standards necessary for submission to a leading, patient-centered, evidence-based medical journal. Use this to re-frame and optimize your research paper before submission.

This comprehensive skill guides authors submitting research to The Burlington Magazine. It outlines the rigorous academic standards required for object-based art history, focusing on connoisseurship, attribution, and provenance. It ensures manuscripts are tightly argued using primary source evidence, technical findings, and close visual examination, helping authors align their work with the journal's specific evidentiary bar and house style.

Provides comprehensive guidelines for designing rigorous technical evaluations for interactive systems, specifically tailored for top-tier venues like UIST. It emphasizes matching evaluation methods to specific artifact claims, reporting distributions over means, closing the interaction loop, and performing thorough ablations against real-world baselines. This framework ensures the scientific rigor and credibility of submitted research.

This skill provides a comprehensive guide for authors targeting the USENIX Symposium on Operating Systems Design and Implementation (OSDI). It helps in positioning complex systems research, covering core scope areas like operating systems, distributed systems, and cloud infrastructure. It details how to frame the contribution, build evidence (artifacts, baselines), and distinguish the work from similar top-tier venues like SOSP and NSDI.

A comprehensive audit checklist for designing and evaluating security experiments, adhering to the highest academic standards (e.g., USENIX Security). It guides users through verifying adaptive attacker models, calculating precision at realistic base rates, ensuring statistical honesty for stochastic results, and maintaining ethical compliance when working with live systems.

This detailed guide helps researchers determine the optimal top-tier venue (e.g., USENIX Security, IEEE S&P, ACM CCS) for their security research paper. It emphasizes that venue selection must be based on the committee's core expertise and the existence of reusable artifacts, measurements, or systems evidence, ensuring the work has the necessary technical depth to succeed.

This guide helps researchers determine if their project qualifies as a visualization contribution (beyond general HCI or ML). It provides structured criteria for choosing the best conference venue (e.g., IEEE VIS, EuroVis, CHI) and mapping the work to one of the six core visualization areas based on contribution type and evidence maturity.

A comprehensive guide for revising visualization research papers for top-tier conferences and journals (e.g., IEEE VIS/TVCG). It mandates shifting focus from aesthetic design to rigorous, task-grounded contributions. Users learn how to justify every visual encoding and interaction based on the analytical task, ensure evaluation methods match the contribution type, and structure the narrative around the data-task problem.

A comprehensive guide for designing and presenting highly rigorous technical evaluations for database or system papers. It covers establishing baseline necessity, proving mechanism causality through ablation, testing scalability across data sizes, and mandating the disclosure of loss cases to satisfy skeptical academic reviewers.

This comprehensive guide teaches researchers how to conduct an exhaustive "reinvention audit" for academic papers, specifically in the database field. It covers searching deep historical literature (pre-2000), modern conference venues (SIGMOD, ICDE), and industrial open-source systems (PostgreSQL, RocksDB) to ensure true novelty and properly position the contribution delta.

A detailed guide for revising academic papers, specifically tailored for systems and database conferences like VLDB. It emphasizes establishing a strong 'page-one contract,' quantifying all performance claims with scoped metrics and baselines, and maintaining rigorous candor regarding design trade-offs and terminology throughout the manuscript.

This comprehensive guide provides researchers with structured methodologies for designing and auditing Computer Vision (CV) experiments for major conferences like WACV. It details the critical differences between the Applications and Algorithms tracks, emphasizing the need to report performance under real deployment constraints (e.g., power, latency) and ensuring fair, rigorous comparisons with baselines. Ideal for revising submissions to meet high review standards.