Skill UI

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 acts as a comprehensive guide for authors targeting the USENIX Symposium on Networked Systems Design and Implementation (NSDI). It helps authors assess the fit of their research in networked, distributed, or cloud systems, providing strategic advice on paper reframing, required levels of evidence (e.g., real-scale deployment), and accurate positioning relative to closely related conferences like OSDI and SIGCOMM. It is a critical tool for optimizing conference submission chances.

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 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.

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.

This comprehensive guide is designed for authors submitting manuscripts in water science or engineering. It details the high standards, scope, and expected rigor for the flagship journal, Water Research. It covers the necessary depth of mechanistic or methodological advances, strict experimental design requirements (including mass balances and controls), and the IMRaD structure required for publication.

Provides comprehensive guidelines for designing and auditing academic tables and figures, specifically for development economics journals. It teaches how to translate statistical coefficients into actionable policy magnitudes, validate research design (e.g., balance checks, pre-trends), and adhere to strict page limits while maintaining clarity for both economists and policymakers.

A detailed guide for structuring and positioning development economics research for high-impact journals like The World Bank Economic Review (WBER). It teaches researchers to reframe their work to satisfy two crucial criteria: rigorous empirical design (credible empirics) and actionable policy relevance in developing countries, ensuring the work transcends being a mere project report.

This router is designed to guide researchers through the complex, multidisciplinary workflow of writing a manuscript for World Development (WD). It helps users determine the correct next step—whether the paper is quantitative, purely qualitative, or mixed-methods—at every stage, from initial topic selection and literature positioning to robust revision, rebuttal, and final submission. It ensures the work meets the high bar of real-world development relevance.

This guide helps scholars rigorously defend the methodological design of academic papers, particularly in International Relations and Comparative Politics. It covers advanced techniques such as process tracing, case selection logic, quantitative cross-national panel data analysis (DID, IV, RDD), and experimental design. Its core purpose is to strengthen causal claims by explicitly addressing selection bias, defining scope conditions, and ruling out major rival explanations.

This guide provides a comprehensive framework for designing rigorous and defensible evaluation sections for machine learning and information retrieval papers, particularly for top-tier conferences like WSDM. It covers the four critical evidence quadrants—Effectiveness, Validity, Efficiency, and Robustness—and details necessary protocols, such as temporal splits, proper baseline selection (including heuristics), ablation studies, and hardware-aware performance reporting. Use this when auditing or writing the experimental section of a research paper.

Biopython is a comprehensive Python library designed for computational molecular biology. It provides robust tools for handling biological sequences (DNA, RNA, Protein), structural analysis (PDB), sequence alignment, phylogenetic tree construction, and interfacing with major public databases like NCBI (Entrez). Ideal for researchers performing advanced bioinformatics tasks.