Skill UI

Provides comprehensive guidelines for authors conducting systematic reviews and meta-analyses in psychology. It emphasizes documenting the literature search protocol, ensuring quantitative synthesis rigor (PRISMA flow, effect-size data), and making all findings open and reproducible for high-impact academic publication.

Provides detailed guidelines for developing tables and figures in Developmental Psychology manuscripts, adhering to APA 7th edition standards. Focuses on making developmental change explicit by using age/time on the x-axis, plotting individual trajectories (spaghetti plots), and displaying model-implied mean curves with confidence intervals, moving beyond simple group mean comparisons.

A comprehensive project management guide for preparing and submitting advanced NLP conference papers to EMNLP. It details the entire research lifecycle, including backward planning from ARR deadlines, managing data annotation timelines, coordinating team roles, and making strategic decisions (commit, revise, withdraw) to ensure successful submission.

This guide provides rigorous standards for developing figures and tables in Earth and Planetary Science Letters (EPSL). It emphasizes making complex scientific arguments legible to a cross-disciplinary audience by mandating visible uncertainty (error ellipses, error bars), providing spatial context, and adhering to strict sub-field conventions (e.g., MSWD, depth scales). It teaches how to structure exhibits so that figures carry the argument, while detailed data resides in the supplementary material.

This guide provides rigorous guidelines for designing and presenting results in Experimental Economics manuscripts. It emphasizes making the treatment comparison and its uncertainty immediately visible through specific figure types (distributions, dynamics plots) and structured tables, ensuring the findings are self-contained and highly credible for academic review.

This guide provides strict guidelines for structuring and presenting empirical results (tables and figures) in financial management manuscripts. It emphasizes making the main coefficient and its practical economic magnitude legible at a glance, adhering to high-standard journal norms (e.g., Wiley/FMA style). It covers best practices for event-study plots, IV tables, and ensuring standard errors and economic significance are always visible.

This guide is designed for authors targeting top-tier journals like Foundations of Computational Mathematics (FoCM). It outlines the journal's high academic standards, requiring deep mathematical rigor, established theorems, and proofs (e.g., convergence, complexity bounds) at the math-computation interface. It emphasizes theoretical foundations over empirical results, making it ideal for advanced research in numerical analysis, optimization theory, and computational geometry.

Provides comprehensive guidelines for designing scientific exhibits, including figures, tables, maps, and Highlights, for interdisciplinary, policy-relevant manuscripts. It emphasizes making data self-contained, focusing on the human/policy dimensions rather than just biophysical trends, and ensuring accessibility across various formats (grayscale, print).

This guide details the strategic process of writing a rebuttal for top-tier academic conferences (such as HRI). It provides a framework for triaging reviewer critiques, addressing methodological concerns (e.g., sample size, confounding), and making credible, actionable promises for the final camera-ready version, all while maintaining academic integrity and anonymity.

This guide details the necessary steps for achieving and reporting reproducibility in Human-Robot Interaction (HRI) studies. Since HRI involves unique elements like human participants and physical environments, reproducibility focuses on making the study protocol, robot behavior specifications, analysis code, and de-identified data transparent. Learn how to properly assemble a comprehensive replication package and ethically disclose limitations to enhance academic credibility in top-tier HRI publications.

This guide outlines comprehensive standards for scientific reproducibility in data engineering. It details best practices for pinning hardware, software, datasets, and variance protocols, ensuring that all performance claims are verifiable and re-runnable by peers, making reproducibility a scored component of academic submission.

A comprehensive guide detailing best practices for creating self-contained, professional, and publication-ready exhibits (tables, figures, matrices) for scholarly manuscripts. It emphasizes making the body text standalone, adhering to journal-specific styles (e.g., APA, JAIS), and presenting complex data (like SEM results) clearly for rigorous peer review.