Skill UI

Structured manuscript and grant review guidance that walks reviewers through methodology, statistics, reporting compliance, and constructive feedback for rigorous scientific evaluation across disciplines.

Compile verified scholarly evidence and references for scientific manuscripts or research briefs. Runs multi-pass Parallel Search with Extract source verification, ranked deduplication, and optional Research/Chat backends to deliver a manuscript-ready research packet targeting 60 unique references.

A comprehensive guide outlining rigorous data analysis and reporting standards for geographic manuscripts. It covers spatial statistics, remote sensing accuracy, and qualitative interpretation, emphasizing spatial honesty, quantifying uncertainty, and ensuring results are robust across different scales and units.

A comprehensive guide for strengthening the methodological design of advanced geographical manuscripts. It covers various paradigms including spatial/quantitative GIScience, remote sensing, qualitative human geography, and mixed methods. Key advice areas include rigorously addressing spatial dependence (MAUP), validating measurements, justifying case selection, and ensuring holistic integration of diverse data sources.

A comprehensive guide for preparing scholarly manuscripts involving spatial data. It outlines best practices for documenting data provenance (sources, projections, processing chains), ensuring reproducibility, and adhering to critical ethical standards such as geoprivacy and human-subjects protection. Essential for maintaining research integrity in academic publishing.

This skill is a comprehensive strategic guide for authors targeting the ACM Conference on Recommender Systems (RecSys). It helps assess the fit of a manuscript, guides the re-framing of work from journal or arXiv styles into a specialized conference narrative, and outlines specific requirements for evidence, evaluation (including offline metrics, user context, and leakage-aware methods), and contribution framing necessary for top-tier CS venues.

A comprehensive strategic guide for authors targeting the ACM International Conference on Multimedia Retrieval (ICMR). This skill helps authors assess the fit of their multimedia retrieval, cross-modal search, or representation learning work for the venue. It provides specific advice on framing the contribution, defining necessary evidence (e.g., ranking metrics, baselines), and structuring the manuscript to meet ICMR's high standards.

A comprehensive guide for authors submitting papers related to web search, ranking, and data mining to WSDM. It provides critical advice on conference fit assessment, proper manuscript re-framing, required evidence (retrieval/ranking baselines, platform-aware evaluation), and how to position the work against competing top venues like SIGIR and KDD.

A comprehensive guide for authors submitting data mining papers to the ACM SIGKDD Conference. It helps authors assess the manuscript's fit, reframe the contribution (e.g., from journal to conference style), and strengthens the evidence bar by focusing on novelty, scale, reproducibility, and clear real-world impact required by top-tier data science venues.

A comprehensive guide for writing and verifying the institutional and accounting standard background section in academic manuscripts. This tool emphasizes the critical need for precision, requiring accurate standard names, official document numbers (文号), effective dates, and applicable scopes. Essential for empirical studies relying on regulatory changes, ensuring the manuscript meets the high standards of authoritative accounting journals.

This comprehensive guide details the methodological requirements for building a robust robustness section in accounting and empirical research manuscripts. It covers four critical pillars: substituting accounting measures, controlling for institutional/governance variables, executing placebo tests, and advanced endogeneity follow-ups. It helps authors ensure their primary findings withstand stringent academic scrutiny.

A comprehensive guide for authors preparing empirical research manuscripts (especially in accounting). It details best practices for structuring main tables (keeping them lean), transforming statistical coefficients into interpretable economic magnitudes, and properly visualizing dynamic effects using event study graphs. It emphasizes moving beyond simple significance stars to provide deep academic context.