Skill UI

A comprehensive guide for executing and reporting advanced analysis for high-level academic manuscripts, particularly in management science. It mandates rigorous verification across two lanes: the analytical lane (proving theorems and comparative statics) and the empirical lane (identifying and estimating causal effects using methods like DiD, IV, and RDD). It emphasizes adherence to Data-and-Code-Disclosure policies, ensuring all results are reproducible, verifiable, and meet high methodological standards.

This guide assists researchers in selecting and rigorously defending the appropriate methodology for Management Science (INFORMS) manuscripts. It covers both analytical modeling approaches (e.g., optimization, stochastic processes, game theory) and empirical designs (e.g., quasi-experiments, field trials). It ensures the chosen design not only matches the research question but also meets strict departmental standards and generates decision-relevant managerial insights.

This guide details best practices for generating self-contained, high-impact exhibits (tables and figures) for academic journals, particularly those with strict page limits like Management Science. It instructs users on structuring both theoretical proofs (analytical lane) and empirical results (e.g., regression coefficients, event-study plots) to ensure the findings are immediately readable and persuasive, even without reading the main text.

A comprehensive guide for structuring the theoretical core of academic papers in Management Science. It covers two main approaches: developing formal analytical models (assumptions, propositions, comparative statics) or generating robust empirical hypotheses based on explicit mechanisms. The goal is always to derive decision-relevant, cross-departmental insights.

A comprehensive guide for executing, evaluating, and reporting the empirical core of MIS Quarterly manuscripts. It covers specialized methods for Behavioral IS (PLS-SEM), Economics of IS (causal identification), Design Science (artifact evaluation), and qualitative studies, ensuring full transparency and replicability for top-tier academic submissions.

This guide outlines the rigorous process for estimating, validating, and interpreting structural models in Marketing Science manuscripts. It covers advanced econometric techniques (GMM, MLE, Bayesian), demonstrating empirical identification, assessing model fit (in-sample/out-of-sample), and computing robust counterfactuals. It ensures the final results are statistically sound, economically plausible, and prepared for replication.

A comprehensive guide for authors packaging their accepted MLSys research artifacts. It details strategies for achieving Availability, Functional, and Reproducible badges by correctly structuring the submission, handling hardware dependencies, and writing the detailed Artifact Appendix. Essential for ensuring scientific claims are independently verifiable.

A comprehensive pre-deadline audit checklist for submitting papers to the MLSys conference. It guides authors through track-specific requirements (Research vs. Industrial), formatting compliance (10-page limit, two-column layout), maintaining double-blind anonymity, and correctly handling appendices and citations to ensure readiness before the submission deadline.

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.

This comprehensive guide outlines the standardized procedures and required repositories for ensuring data and code availability in scientific publications, particularly in molecular biology. It details where to deposit various data types (e.g., sequencing, structures, proteomics) in approved archives (GEO, PDB, PRIDE, Zenodo), provides the mandatory standardized statement format, and emphasizes the need to obtain accessions/DOIs before submission to ensure reproducibility.

A comprehensive, step-by-step preflight checklist designed for authors submitting manuscripts to top-tier scientific journals. It ensures thorough validation across all required components, including the mechanistic narrative, structural data integrity, statistical rigor (QSA), figure quality, and proper data/code deposition (DOIs). It serves as the ultimate gatekeeping mechanism before final submission.

This skill assesses the suitability and required rigor of a manuscript for the Molecular Biology and Evolution journal. It provides comprehensive guidelines covering specific scopes (e.g., population genetics, phylogenetics, positive selection), necessary methodological standards (including uncertainty quantification and addressing selection bias), and structural requirements for high-impact submissions in molecular evolution and genomics.