Skill UI

A comprehensive guide for conducting advanced, methodologically rigorous data analysis for manuscripts in Entrepreneurship Theory and Practice (ETP). It covers specialized techniques such as survival analysis, handling endogeneity (IV, selection bias), advanced panel data models (Callaway–Sant'Anna), and rigorous qualitative coding schemes. The goal is to ensure that findings are theoretically robust and translate into actionable, venture-relevant insights, moving beyond simple p-value reporting.

A comprehensive guide for analyzing and reporting findings in entrepreneurial research, specifically tailored for high-level academic journals. It covers advanced econometric techniques necessary to address common data challenges in venture panel data, such as survivorship bias, selection into founding, endogeneity, and attrition. It ensures methodological rigor and robust reporting.

A comprehensive guide for authors submitting to machine learning conferences like NeurIPS. It details the rigorous standards for data splitting, hyperparameter reporting, random-seed protocols, and compute transparency required for a main-track paper. It also helps authors strategically decide between the main track and the MLRC/TMLR routes based on their core contribution (replication vs. novelty).

This guide provides a comprehensive framework for designing rigorous and defensible evaluation sections for machine learning and information retrieval papers, particularly for top-tier conferences like WSDM. It covers the four critical evidence quadrants—Effectiveness, Validity, Efficiency, and Robustness—and details necessary protocols, such as temporal splits, proper baseline selection (including heuristics), ablation studies, and hardware-aware performance reporting. Use this when auditing or writing the experimental section of a research paper.

This skill structures free-text adverse event narratives into the mandatory ICH E2B(R3) format. It populates critical fields required for regulatory submissions (like FAERS/EudraVigilance), including suspect drugs, reactions (mapped via MedDRA), seriousness criteria, and reaction outcomes. Use it when generating Individual Case Safety Reports (ICSRs) from clinical narratives.