Skill UI

A comprehensive guide for authors submitting to SCI journals, detailing best practices for making research code and data available. It addresses how to proactively provide reproducible materials, structured documentation, and honest availability statements, even when formal 'Artifact Evaluation' badges are not mandatory. It helps authors improve the robustness and impact of their scientific findings.

This skill guides authors on positioning information retrieval (IR) work for the Text REtrieval Conference (TREC). It functions as a venue-selection and manuscript re-framing tool, ensuring the submission aligns with TREC's focus on shared evaluation tracks, test collections, and NIST-style benchmarking. It helps authors structure evidence, understand reviewer expectations, and distinguish the work from general CS conference submissions.

A comprehensive tool for assessing whether an econometric manuscript is suitable for submission to The Econometrics Journal (EctJ). It guides authors through evaluating methodological novelty, theoretical rigor, structural compliance, and adherence to high academic standards, covering everything from new estimators and inference procedures to house style and potential desk-reject risks. Use this skill when targeting a highly specialized economic journal or needing to re-frame an applied study into a theoretical methods contribution.

This skill provides a comprehensive framework for evaluating whether a clinical medicine or global-health manuscript is suitable for publication in The Lancet. It guides authors on refining the manuscript's framing, ensuring methodological rigor (e.g., PRISMA, STROBE), and adhering to the journal's specific house style and high editorial standards related to global health and health equity.

A comprehensive guide to assessing whether a mental health or psychiatry study is suitable for publication in The Lancet Psychiatry. It details the journal's high standards, focusing on large-scale population/epidemiological analyses, policy relevance, and rigorous methodology (e.g., RCTs, cohort studies). The skill helps authors re-frame their research question to meet global health and system-level impact requirements, covering reporting guidelines (CONSORT/STROBE/PRISMA) and submission structure.

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.

A comprehensive guide detailing the standards for scientific reproducibility in visualization research, particularly for IEEE VIS submissions. It outlines the Graphics Replicability Stamp Initiative (GRSI) requirements, covering how independent volunteers must reproduce results using provided code, data, and environments (e.g., Docker containers). Learn how to package your work—including determinism aids, mapping tables, and licensed data—to pass rigorous, clean-machine testing.

A comprehensive guide for designing and auditing visualization experiments for high-stakes academic submissions (e.g., IEEE VIS). It details how to match evidence—such as controlled studies, power analyses, and benchmarks—to the specific type of claim (perceptual, algorithmic, system). Learn best practices for statistical rigor, CVD-safe encoding, and maintaining full provenance to ensure your findings are scientifically sound and trustworthy.

This guide outlines the methodology for preparing research artifacts for rigorous academic reproducibility evaluations, such as those run by VLDB/SIGMOD. It details the required components—including prototype code, input data, workloads, and analysis scripts—to structure a comprehensive package. The goal is to ensure that any external evaluator can independently and flawlessly rebuild and validate all claimed results, maximizing the chances of winning reproducibility awards.

Provides comprehensive guidelines for packaging and submitting research artifacts (datasets, models, code) for major conferences. It details the difference between mere 'existence' (badge verification) and true academic 'reproducibility,' covering archival strategies, web data licensing, takedown resilience, and minimal viable package structure for long-term scholarly impact.

This skill is a specialized guide used by authors to evaluate the fit and required rigor for submitting development economics manuscripts to the World Bank Economic Review (WBER). It assesses the manuscript's alignment with the journal's focus on policy-relevant empirical micro and macro research, covering methodological standards (RCTs, IV, DiD), required policy framing, and structural formatting.

This comprehensive guide outlines best practices for packaging research artifacts, including code, proprietary data logs, and models, for submission to top-tier academic venues. It addresses the crucial need for verifiability and reproducibility, providing strategies for handling limited space, proprietary datasets, and the absence of formal artifact grading systems, ensuring high academic credibility.