Skill UI

This comprehensive guide provides a detailed audit checklist for submitting research manuscripts to major design automation conferences (e.g., DAC). It covers critical steps such as the two-stage abstract/manuscript timeline, adherence to the strict 6+1 page format, ensuring double-blind anonymization (removing all identifying metadata), declaring TPC conflicts, and mitigating common submission risks. Essential reading for researchers preparing for high-stakes academic submissions.

This comprehensive guide assists researchers and practitioners in selecting the optimal venue and track (e.g., DAC, ICCAD, ISCA) for their electronic design automation (EDA) or chip-design project. It clarifies the critical distinction between the archival Research Manuscript track and the industry-facing Engineering Track at DAC, emphasizing the need to frame contributions using measurable Quality of Results (QoR) improvements, novel algorithms, or real-world industrial lessons.

This guide assists users in structuring and rigorously defending the methodological design for demographic manuscripts. It provides detailed guidance on selecting and justifying advanced techniques—including life tables, decomposition analysis, survival models, Age-Period-Cohort (APC) modeling, and microsimulation. It emphasizes critical steps like establishing identification assumptions, addressing causal biases (selection and exposure), and formulating an adjudication test to rule out rival explanations, ensuring the research is methodologically robust.

This tool serves as the comprehensive orchestrator for manuscripts submitted to Demography (PAA). It guides authors through the entire population science publishing lifecycle. By assessing the manuscript's current stage (e.g., topic selection, research design, data analysis, rebuttal) and determining the appropriate article type (Research Article, Note, or Commentary), it routes the user to the next specialized skill or writing phase required for successful submission.

A comprehensive planning tool for developmental psychology researchers designing studies that must support a claim of change. It systematically guides users through critical methodological issues, including addressing age vs. cohort confounds, planning for measurement invariance across ages, handling attrition, and properly justifying sample size for growth slopes. Essential for strengthening the pre-analysis plan of longitudinal and cross-sectional designs.

This comprehensive guide helps researchers determine if their empirical project qualifies for a Developmental Psychology journal. It emphasizes that the core contribution must focus on 'developmental change' across the lifespan (age effects, trajectories, or underlying mechanisms), rather than merely describing a single-age phenomenon. It provides a four-gate fit test covering developmental claims, theory advancement, design credibility, and open-science readiness, guiding researchers on framing and proper submission tiering.

This comprehensive checklist is designed for auditing NLP research papers, particularly for major conferences like EACL. It serves as a claims audit, ensuring that every reported result, claim, or finding—including hyperparameters, compute costs, verbatim prompts, data sources, and significance testing—is fully documented and reproducible. It emphasizes academic rigor and transparency in AI research.

A comprehensive skill guide designed to help researchers assess the suitability of their economics manuscripts for submission to 《Economic Review》. It covers journal positioning, required empirical rigor, structural expectations (abstract, citation style), common rejection pitfalls, and advice on necessary revisions and alternative journals. This tool is crucial for navigating academic publishing standards in Chinese economics.

A comprehensive router designed to guide researchers through the entire lifecycle of writing a highly rigorous academic paper for top-tier econometrics journals, such as Econometrica. It outlines the necessary steps—from initial topic selection and theoretical positioning to detailed identification checks, robustness testing, and final submission package assembly—ensuring the manuscript meets the highest standards of mathematical rigor and scholarly depth. This guide does not replace specialized skills but dictates the optimal sequence of research stages.

This guide provides comprehensive standards for conducting and reporting rigorous empirical and simulation evidence in econometrics. It covers designing Monte Carlo simulations, creating minimum evidence maps, ensuring reproducibility through detailed logging, and linking theoretical claims directly to finite-sample evidence. Essential for high-level statistical research.

This guide provides comprehensive instructions for creating a robust, reproducible artifact package for database systems research. It details best practices including containerization, pinning workloads, generating a permanent DOI-archived record, and designing the package to be successfully built and demonstrated on a reviewer's clean machine within a tight time budget. The goal is to strengthen scientific rigor and ensure permanent, open-access citation.

This guide provides comprehensive standards for designing, auditing, and reporting empirical evaluations in database systems research. It emphasizes the principle that evidence must proportionally match the claim, requiring the use of real-world workloads, fair and tuned baselines, thorough measurement of variance and state (warm/cold), and fully reproducible evaluation harnesses. It also outlines the higher bar for 'Experiments & Analysis' papers.