Skill UI

This comprehensive guide assists authors in determining if their molecular biology manuscript is optimally suited for Molecular Cell. It scrutinizes the necessary depth of mechanistic resolution, the required structural or biochemical evidence, and adherence to rigorous academic standards. It covers journal positioning, scope fitting (e.g., transcription, chromatin), and mandatory methodological components like STAR Methods and data deposition, ensuring authors meet the journal's high expectations.

This comprehensive guide assists researchers in determining the suitability of their manuscript for Nucleic Acids Research (NAR). It details the journal's scope, structural demands, and rigorous standards for submissions involving DNA, RNA, bioinformatics, databases, or web tools. Use this to assess the fit and required elements before official submission.

This skill guides authors on strategically positioning data mining research for the SIAM International Conference on Data Mining (SDM). It helps adjust manuscript framing, emphasizing mathematical rigor, statistical depth, and algorithmic contribution suitable for top Computer Science venues. Use it for venue selection, understanding reviewer expectations, and structuring evidence to meet the high standards of SIAM-style research.

This guide provides researchers with a critical framework for determining if their work on algorithms, data structures, and discrete mathematics is suitable for SODA (ACM-SIAM Symposium on Discrete Algorithms). It outlines a rigorous three-question fit test, offers a routing map to comparable specialized venues (like STOC or FOCS), and clarifies the specific academic pattern required for a submission to be considered novel and impactful to an algorithms expert.

A comprehensive guide for structuring and positioning computer science manuscripts for The Web Conference (WWW). It advises authors on leveraging open-web data, focusing on web systems, web mining, and responsible AI, while adhering to the latest venue-specific standards and evidence requirements.

This tool acts as the central orchestrator for academic manuscripts submitted to World Politics. It guides authors through the entire scholarly writing lifecycle, determining the correct article type (research vs. review), verifying the scope (must cross cases in comparative politics/IR), and routing the project to the appropriate specialized writing skills (e.g., theory building, data analysis, literature positioning). It ensures the work maintains a big, comparative, and international scope.

A comprehensive framework for ensuring reproducibility in Web Search and Data Mining (WSDM) research. It addresses unique challenges associated with behavioral data, covering data provenance, temporal splitting discipline, bias assumption reporting, statistical rigor (seeds, variance), and the 'honesty ladder' for non-reproducible results, helping researchers publish robust and verifiable work.

A comprehensive guide detailing the rigorous, multi-stage academic review process for top-tier data mining conferences (e.g., WSDM). It analyzes the hybrid single/double-blind architecture, the impact of no rebuttal phase, and the distinct perspectives of academic and industry reviewers. Use this guide to understand the requirements for writing and structuring submissions that maximize acceptance chances.

A comprehensive guide for researchers to evaluate if their project aligns with the niche scope of WSDM. It details the 'two-gate test' (web/social data focus and practical/principled approach) and provides a routing table to help authors determine the most appropriate conference venue (e.g., SIGIR, KDD, RecSys) for their work.

This skill programmatically searches and fetches biomedical literature from PubMed and PMC using NCBI E-utilities (ESearch, EFetch, ESummary). It allows users to gather large corpora of abstracts, full texts, and metadata related to specific conditions, drugs, or genes. Ideal for building evidence bases, performing biomedical Named Entity Recognition (NER), or summarizing scientific findings.

This skill calculates and documents the residual re-identification risk of de-identified datasets. It goes beyond simple direct identifier removal by assessing the risk posed by quasi-identifiers (age, ZIP, dates). It computes structural metrics like k-anonymity and l-diversity, and runs empirical linkage attacks to provide a defensible memo supporting HIPAA Expert Determination for determining if a dataset is safe for release.

This tool provides a statistically rigorous framework for analyzing a user's private LinkedIn post performance data. It moves beyond simple averages, utilizing median/MAD and permutation testing to determine if observed patterns are genuine or statistical noise. It guides users through three steps: descriptive analysis, pattern mining, and sizing future A/B experiments, ensuring hypotheses are testable and avoiding over-conclusion. Works only with your own exported data.