Skill UI

This guide provides detailed instructions on writing the policy implications section for manuscripts submitted to quantitative journals (like JQTE). It emphasizes grounding all policy recommendations in the paper's specific quantitative findings (measurement, forecasting, or decomposition results), ensuring the advice is actionable, timely, and relevant to planning, industry, and technology decisions.

A comprehensive guide for structuring the empirical section of high-level machine learning papers (e.g., KDD). It details the 'four-axis evidence plan'—Quality, Scale, Efficiency, and Mechanism—and emphasizes critical data hygiene practices. Learn how to prevent temporal leakage, structure ablations in a matrix format, and design post-launch measurements to ensure academic rigor and reproducibility.

A comprehensive project management guide for planning submissions to KDD, accounting for its unique structure of two annual submission cycles. It covers milestone tracking, cycle-choice decision matrices, managing the Resubmit loop, and planning evidence lead times from abstract to camera-ready status. Essential for complex, multi-stage data science research.

Provides detailed guidelines for creating high-standard clinical figures and tables, modeled after leading medical journals (e.g., The Lancet). It covers essential display items including Table 1 (baseline characteristics), Kaplan-Meier survival curves (with numbers-at-risk), Forest plots for meta-analyses, CONSORT/PRISMA flow diagrams, and global maps. The guide emphasizes the rigorous reporting of 95% confidence intervals (CIs) and proper statistical methods to ensure scientific accuracy.

A comprehensive guide for auditing and planning the analysis of linguistic manuscripts. It emphasizes that the analysis must credibly support the theoretical claim, covering quantitative modeling (mixed-effects models in R), phonetic measurements, and corpus statistics. Use this skill to stress-test the analysis chain, ensuring rigor and transparency in all generalizations.

This guide provides a structured framework for authors responding to academic peer review decisions (R&R or Rejoinder). It transforms scattered reviewer objections into a cohesive, point-by-point revision plan. The process emphasizes engaging fairly with all criticism, strengthening claims with new data or predictions, and openly reconciling conflicting academic viewpoints.

Systematically transforms high-level ideas or goals into a detailed, structured, and executable taskbook designed for AI agents. This process involves deep research, validation against existing codebases, adherence to strict formatting rules, and generating a single, copy-pastable block of instructions for immediate agent execution. It distinguishes between execution and exploration tasks, ensuring all steps are verifiable and anti-cheating measures are included.

This guide details the complex, multi-stage review process for high-level academic journals, such as Management Science. It explains critical stages like department-specific desk screening, double-anonymous refereeing, and assessing cross-departmental fit. It is essential for authors who need to understand how submissions are evaluated, interpret rejection letters (e.g., fit vs. rigor), and plan their next steps for revision or re-aiming.

A comprehensive guide for structuring and defending the methodology section of an academic manuscript, particularly for MIS Quarterly submissions. It helps researchers choose the appropriate design (Behavioral, Design Science, Economics of IS, Organizational) and addresses critical methodological rigor, such as causal identification, common-method bias, and thorough evaluation planning.

A comprehensive project management guide for the MLSys conference submission cycle. It covers the entire research lifecycle, from initial venue selection and track choice through paper submission, review responses, artifact evaluation, and final conference presentation. The guide emphasizes backward planning, managing critical resources like shared GPU time, and mitigating common failure modes.

This guide walks authors through the critical steps of transitioning an accepted academic paper from an anonymous submission to the final, published, double-column camera-ready version. It covers de-anonymization (restoring author details, links), fulfilling all review promises, completing ACM metadata and rights, coordinating artifact badges, and planning the in-person conference presentation.

This guide helps authors navigate the complex, multi-stage submission process for MobiCom. It emphasizes planning backward from the final paper cutoff, accounting for two distinct annual rounds, staggered review stages, and the critical impact of schedule slips on program editions. Essential for managing wireless and mobility research timelines.