Skill UI

This guide provides best practices for structuring complex academic manuscripts, particularly for conferences requiring a single-PDF submission model. It details how to optimally split content between the limited body (e.g., 12 pages) and the extensive appendix, ensuring that the crucial theorems, proofs, and auxiliary lemmas are presented in a verifiable and highly readable manner for peer reviewers. Key techniques include implementing restatement discipline and writing roadmap paragraphs for clear verification paths.

A comprehensive guide for developing scientifically rigorous, APA-formatted tables and figures for quantitative communication research. This skill emphasizes that exhibits must be self-contained, displaying effect sizes and uncertainty (not just significance stars), and following strict reporting standards for maximum clarity for reviewers.

A comprehensive guide for hardening deep learning papers, particularly in Computer Vision (CVPR). It details best practices for achieving rigorous reproducibility by utilizing the Compute Reporting Form (CRF), maintaining a detailed recipe ledger, ensuring benchmark split hygiene, and meticulously documenting all training hyperparameters, seeds, and variance analyses for 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 specialized guide for polishing academic manuscripts, particularly in econometrics and theoretical sciences. It enforces a terse, formal, and highly structured writing style, ensuring all definitions, assumptions, and theorems are numbered and displayed correctly. Ideal for turning narrative drafts into submissions suitable for top-tier academic journals.

This guide provides strict guidelines for authors submitting econometrics papers, detailing how to strategically compress, optimize, and structure academic exhibits (tables, figures, simulations). It ensures that critical results and diagnostic information are presented clearly within tight page constraints, maximizing impact while adhering to journal standards.

This guide helps researchers evaluate whether their computer systems project—covering areas like OS, distributed infrastructure, cloud computing, and ML systems—is best suited for EuroSys, or if it should target other top-tier venues like SOSP, OSDI, or ASPLOS. It provides rigorous criteria covering built artifacts, transferable ideas, evidence quality, and strategic timing to maximize publication chances.

Provides rigorous guidance and structure for statistical analysis in Field Crops Research (FCR). Focuses on implementing linear mixed models that respect complex experimental designs (e.g., split-plot, block, environment). Essential for proper G×E analysis, robust means separation, and accurate evaluation of crop models, ensuring results are methodologically sound and actionable.

Provides essential guidelines for designing rigorous, generalizable field experiments in crop research. Covers multi-environment trials (MET), proper randomization, blocking strategies, split-plot designs, and Genotype-by-Environment (G×E) analysis. Use this tool when planning or defending the scientific rigor of an agricultural manuscript.

Genomic Intelligence provides powerful, hosted transformer models for advanced genomic analysis. Users can input a DNA/FASTA sequence and receive structured predictions for key regulatory features, including promoter regions, splice sites, enhancer activity, chromatin state, gene expression (log TPM), and de-novo gene annotation. This service operates via a REST API or MCP server, eliminating the need for local GPU hardware or model weights, making complex bioinformatics accessible through sequence input.

This guide helps researchers determine the most appropriate conference venue (e.g., HPCA, ISCA, MICRO, ASPLOS) for their microarchitecture or systems research paper. It outlines key criteria, such as whether the contribution is a measured microarchitectural cost, a buildable mechanism, or a measurable characterization, and how to strategically route the project based on its novelty and evidence.

A comprehensive guide for generating and packaging reproducible evidence for signal processing submissions to ICASSP. It details what reviewers prioritize (scoring scripts, dataset splits, logs) and outlines best practices to ensure that headline metrics are easily regenerated, thereby maximizing review credibility and post-publication impact.