Skill UI

This comprehensive guide details the rigorous methodology for designing, executing, and reporting experimental results in Information Retrieval (IR). It covers best practices for selecting appropriate test collections, choosing defensible metrics, performing proper statistical significance testing (e.g., paired t-tests), ensuring baseline fairness, and proactively addressing modern pitfalls like LLM contamination. Essential for publishing high-quality, auditable research in IR/NLP.

A comprehensive audit checklist designed for authors submitting papers to the SIGIR conference. It guides users through critical pre-submission checks, covering adherence to specific full/short paper formats, mandatory anonymization techniques (e.g., stripping system names, log provenance), cross-track submission rules, AI disclosure requirements, and common pitfalls that lead to desk rejection.

A comprehensive guide designed for planning major academic conference submissions (e.g., SIGIR). It provides a detailed backward-planning calendar, mapping milestones from initial scoping and evidence building through to final camera-ready submission and presentation. This tool helps researchers manage complex multi-track coordination, identify potential failure modes, and utilize fallback conference pathways.

This comprehensive guide outlines best practices for designing data systems evaluations, ensuring results are robust, reproducible, and convincing to expert reviewers. It covers workload realism, baseline fairness, necessary ablation studies, and advanced metric visualization techniques (e.g., sweeping curves, failure analysis) required for top-tier data systems research.

This comprehensive guide provides methodological frameworks for designing rigorous empirical studies in strategic management. It covers defining the sample, selecting the unit of analysis, validating key measures (performance and strategic choices), and critically, implementing robust identification designs (e.g., DID, IV, Fixed Effects) to address endogeneity and establish causal claims.

This workflow router is designed for academic researchers targeting top-tier strategy journals. It does not write the paper but acts as a systematic guide, analyzing the current state of your manuscript—from vague ideas to final submission—and recommending the precise next specialized skill needed. It ensures that the paper is systematically improved across theory development, methodological rigor, data analysis, and contribution framing, guiding the author through the entire publication lifecycle.

A comprehensive guide designed for the late-stage polishing of academic manuscripts, specifically targeting submissions to top-tier journals. It focuses on enhancing clarity, improving argument flow, adhering to strict academic house conventions (such as dual abstracts and APA style), and refining prose. This skill ensures the research contribution is clearly articulated and immediately visible to the reader, optimizing the structure and polish of the final paper.

A comprehensive guide for designing rigorous Monte Carlo simulation studies, particularly for methods-heavy academic submissions (e.g., SMR). This guide covers specifying the Data Generating Process (DGP) space, selecting non-negotiable competitor methods, choosing appropriate performance metrics (e.g., power, bias, coverage), and critically reporting the limitations and failure regimes of the proposed method to ensure maximum credibility and reproducibility.

Provides expert guidelines for creating high-rigor methodological exhibits for the Sociological Methods & Research (SMR) journal. Focuses on constructing self-contained simulation grids, method-comparison tables, and diagnostic figures that clearly communicate methodological arguments, ensuring reviewers can audit claims directly without relying on surrounding prose.

This guide provides comprehensive best practices for designing and auditing cloud system evaluations, particularly for academic submissions. It mandates that claims must be supported by measured evidence from real or realistic deployments, moving beyond simple simulations. Key metrics emphasized include tail latency (p99), operational cost modeling, and verifiable behavior under scale and multi-tenancy.

A comprehensive pre-submission checklist designed for academics submitting manuscripts to scholarly journals. It covers crucial formatting rules, such as specific citation styles (Author-Date), bibliography standards (GB/T 7714), appropriate use of footnotes, abstract/keyword length limits, and guidelines for maintaining anonymity during the review process. Essential for ensuring submissions meet strict academic publishing requirements.

A comprehensive guide for constructing non-empirical, theoretical figures for sociological theory manuscripts. It details how to design conceptual exhibits—including mechanism diagrams, process models, typologies, and concept maps—that carry theoretical work. Crucially, it emphasizes that these figures must illustrate mechanisms or classifications, and must never include raw data, regression tables, or empirical results.