Skill UI

A rigorous pre-writing framework used by researchers to stress-test a study's significance against the high standards of top-tier medical journals (e.g., The Lancet). It assesses whether the work is clinically important, globally relevant, likely to change policy, and addresses health equity, preventing wasted research efforts on unsuitable manuscripts.

A mandatory skill for original research articles, designed to create The Lancet's signature 'Research in context' panel. This panel forces authors to synthesize their findings within a systematic evidence base by detailing what was known previously (with documented search strategies), outlining the specific added value of the current study, and discussing the collective implications for clinical practice and public health policy.

A comprehensive routing tool designed to guide authors through the entire lifecycle of a clinical or global-health manuscript intended for submission to The Lancet. It diagnoses bottlenecks and suggests the next specialized skill to use, ensuring the manuscript meets high standards of clinical importance, global relevance, and policy impact. It covers stages from initial concept and design to reporting, writing, and rebuttal.

A comprehensive skill designed to help researchers assess whether a manuscript is suitable for submission to the prestigious journal, Macroeconomics. It covers the journal's scope (macro-policy, growth, regional strategy), required methodological rigor (econometrics, model transparency), structural expectations, and common pitfalls, acting as a pre-submission positioning and rewriting framework.

This skill guides researchers in determining the suitability of their social science, economics, or management manuscript for submission to *Management World*. It provides detailed guidance on journal positioning, required structural elements (focusing on Chinese institutional context and actionable policy advice), and outlines common pitfalls and necessary revisions before formal submission.

This comprehensive guide outlines the mandatory replication and data policy for mathematical finance manuscripts. It provides authors with templates for Data Availability Statements (covering no data, code only, or public data) and details rigorous best practices for ensuring numerical exhibits are fully reproducible. It covers creating exhibit provenance ledgers and managing computational dependencies to maintain academic rigor.

A comprehensive guide for structuring and generating core exhibits—including estimates, model-fit, comparative statics, and counterfactuals—for academic manuscripts in Marketing Science. Designed to adhere to rigorous academic house styles (e.g., INFORMS), ensuring model mechanisms and policy implications are clearly and rigorously presented to quantitative reviewers.

This skill provides comprehensive guidance for authors targeting *Modern Economic Research*, a top-tier journal focused on comprehensive economic theory. It outlines the journal's academic scope, including industrial policy, digital economy, and regional reform. The guide emphasizes the need for manuscripts to possess strong institutional logic, verifiable evidence, and theoretical contribution, ensuring the work transcends mere policy reports.

A comprehensive guide and framework for authors targeting the journal 'Modern Financial Research'. It helps assess whether a manuscript's scope, methodology (e.g., VAR, DID), and policy relevance align with the journal's focus on banking, finance, and macro-policy. It details submission requirements, common pitfalls, and suggestions for revision or alternative journals.

A comprehensive guide for structuring and presenting complex analytical and empirical results for Operations Management journals (M&SOM). It emphasizes strict formatting rules, adhering to a hard page limit, and ensuring that all exhibits are self-contained and immediately convey the core insight (e.g., plotting policy structures, highlighting operational magnitudes, and using automated tools for generation).

A guide for developing rigorous analytical or stochastic models for Manufacturing & Service Operations Management (M&SOM). It emphasizes translating operational decisions, objectives, and uncertainties into explicit structural results, such as policy forms (e.g., order-up-to levels) and comparative statics, ensuring the core insight remains operational rather than merely descriptive.

A comprehensive guide for building robust causal identification strategies in empirical research, particularly for analyzing policy shocks. It provides best practices and checklist items for advanced econometrics methods like Difference-in-Differences (DID), Instrumental Variables (IV), Regression Discontinuity (RDD), and Double Machine Learning (DML), helping researchers avoid common methodological pitfalls in top-tier academic publications.