Skill UI

This module provides minimal working examples for the OpenEvidence API, designed for clinical intelligence applications. Users can perform complex clinical queries to get treatment recommendations, check potential drug interactions based on patient context, and search for authoritative medical guidelines from major health organizations (e.g., ACC/AHA). Ideal for developing evidence-based healthcare decision support systems.

This guide provides a methodology for integrating theoretical models into empirical economics papers, especially for journals emphasizing empirical findings (e.g., AEJ: Applied). It teaches researchers how to ensure that theoretical components—such as mechanisms, welfare statements, or counterfactuals—serve to interpret, sharpen, or guide the existing empirical estimates, rather than leading the paper or replacing the core identification provided by the design. Focus on sufficient statistics and minimal model assumptions is key.

This guide provides a methodological framework for drastically streamlining complex academic models, whether theoretical or structural/empirical. It teaches how to Strip assumptions, retain only the necessary components, and present the argument such that the entire paper focuses on delivering one distinct, surprising insight. Generalizations and lengthy proofs belong in the appendix, keeping the main text maximally focused and concise.

This tool guides researchers in selecting and rigorously stress-testing appropriate methodologies (quantitative, qualitative, or normative) for public administration manuscripts. It ensures methodological alignment with the core research question, providing detailed checks for causal inference techniques (DID, IV, RDD) and qualitative rigor, thereby strengthening the overall academic argument.

A comprehensive guide for ensuring rigorous statistical inference in experimental economics. It covers critical areas such as power justification, determining the correct unit of observation (cluster-robust SEs), handling multiple comparisons, and applying non-parametric tests. This framework helps researchers transition from preliminary findings to statistically robust, publishable conclusions.

This skill provides a rigorous academic review framework for determining if a research paper significantly advances the frontiers of game theory and its applications. It assesses conceptual advances, mechanism design robustness, behavioral novelty, and cross-field reach, guiding authors on whether their work meets the high standards of top-tier academic journals like GEB. Ideal for assessing high-level theoretical or empirical contributions.

This comprehensive guide outlines the strict requirements and protocols for submitting papers to the IEEE International Conference on Data Mining (ICDM). It details the crucial differences between the Research and Applied tracks, emphasizing the triple-blind anonymity regime. Key points include adhering to the strict 10-page IEEE format (including references and appendices), avoiding identity leaks in the body or metadata, and understanding the single, non-negotiable submission deadline. Failure to follow these guidelines results in automatic rejection.

This guide assists researchers in determining the best fit for their data mining research project. It compares the contribution against major conferences (ICDM, KDD, SDM, etc.) and helps decide the appropriate track (Research, Applied, Blue Sky) based on the nature of the mechanism, evidence, and intended scope for optimal academic impact.

A comprehensive guide for researchers submitting academic papers to ensure high standards of reproducibility and verifiable evidence. It covers critical areas such as data-availability statements, artifact management, provenance pinning (for LLMs and mining), and mapping claims directly to evidence, adhering to rigorous academic standards.

This guide provides comprehensive strategic advice for authors targeting the IEEE Visualization Conference (IEEE VIS). It covers conference positioning, scope fitting, required evidence (visual encoding, evaluation), and helps authors re-frame their work from journal or arXiv formats into a selective, high-impact conference narrative. Use it when determining if a research manuscript is appropriate for IEEE VIS.

This guide provides best practices for structuring tables and figures in academic econometrics manuscripts, especially when adhering to strict journal page limits. It advises researchers on exhibit triage—determining which core findings belong in the main text versus supplementary online appendices—and guarantees reproducibility by detailing required note components and generating scripts.

This skill helps authors evaluate if their empirical work—which applies econometric methods to substantive economic questions—is suitable for top-tier applied econometrics journals. It guides authors on the necessary focus on empirical application, data reproducibility, methodological rigor, and proper framing, helping authors minimize rejection risks and select the best publishing venue.