Skill UI

A comprehensive guide for conducting advanced quantitative research using Structural Equation Modeling (SEM) on questionnaire data. It details rigorous procedures for testing complex causal relationships, including mediation, moderation, and moderated mediation, alongside handling nested data via Hierarchical Linear Modeling (HLM). Essential for academic papers requiring robust inference.

A comprehensive guide detailing the high standards required for presenting security evidence at major conferences. It covers methodologies for proving claims—including attacks, defenses, and detection systems—across live internet measurements, controlled testbeds, and emulation. Key requirements include adaptive adversary modeling, rigorous measurement hygiene, and adherence to ethical review protocols to ensure results are reproducible and relevant to real-world networks.

This guide helps authors structure highly technical security papers, especially for venues with strict page limits like NDSS. It details how to allocate content across the main body, ethics considerations, and appendices, ensuring the core decision-making arguments remain self-contained and maximally persuasive to reviewers by passing the 'dependency test'.

A comprehensive guide for security researchers to determine the optimal top-tier conference venue for their paper. It provides structured 'fit tests'—including the wire test, deployment envelope test, and adversary ownership test—and a routing table to assess whether the work belongs at NDSS, IEEE S&P, USENIX Security, or related venues, maximizing the chance of successful publication.

This skill rigorously stress-tests a clinical study's potential impact against the standards of top-tier medical journals (e.g., NEJM, Lancet, JAMA). It evaluates three critical gates: clinical importance (patient outcomes), methodological rigor (study design), and generalizability (broader applicability). Use this to determine if a study is merely incremental or if it genuinely sets a new standard of care, helping authors decide the best publication venue.

This skill acts as a central router for manuscripts targeting The New England Journal of Medicine (NEJM). It does not replace specialized skills but rather diagnoses the current stage of a clinical manuscript—from initial significance testing to response to reviewers—and directs the user to the correct subsequent skill (e.g., nejm-fit, nejm-study-design). It outlines the rigorous workflow, necessary checks, and structural differences required for submission to top-tier clinical journals.

A comprehensive guide for stress-testing the evidence supporting ML claims before submitting to top-tier academic conferences. Covers rigorous auditing of baselines, ablation studies, robustness checks, data leakage, and calibrating claims against evidence strength, ensuring scientific reproducibility.

This guide provides a framework for assessing whether a research topic is suitable for interdisciplinary journals focusing on digital media and society (like NM&S). It details a four-part fit test, ensuring the research has social stakes, a portable concept, interdisciplinary reach, and enduring relevance beyond the news cycle. It helps researchers reframe narrow case studies into broadly applicable scholarly arguments.

A comprehensive guide for authors preparing accepted academic papers for artifact evaluation at major conferences (e.g., NSDI). It details how to package code, traces, and testbed recipes to ensure permanent public availability, achieve recognition badges (Functionality, Availability, Reproducibility), and meet community award criteria. Learn best practices for reproducibility and structured submission.

This comprehensive guide assists reviewers and authors in determining the most appropriate venue for programming language research within the SIGPLAN community. It provides a detailed 'center-of-mass' test, helping categorize contributions based on whether they emphasize metatheory (POPL), performance engineering (PLDI), functional techniques (ICFCP), or the broad design scope characteristic of OOPSLA. It guides the decision-making process for academic submissions.

This guide assists in the rigorous development of theoretical frameworks for Organization Science manuscripts. It details the two legitimate modes—deductive (a priori) or inductive (grounded)—and emphasizes the critical need to identify the core organizational mechanism, specify the levels of analysis (micro, meso, macro), and articulate cross-level bridging logic and boundary conditions. It guides users beyond simple literature reviews to build genuine, testable theory.

This guide helps researchers determine if their problem constitutes a rigorous Operations Research (OR) or Management Science (MS) methodological contribution. It provides a comprehensive fit test covering method novelty, mathematical rigor (proofs, guarantees), and significance to the OR community. Furthermore, it guides users on selecting the precise editorial area (e.g., Optimization, Stochastic Models, Simulation) for submission.