Skill UI

This skill helps authors determine if their manuscript is suitable for the International Conference for High Performance Computing, Networking, Storage and Analysis (SC). It provides comprehensive guidelines on framing the work, establishing the evidence bar (requiring scale, performance portability, and systems impact), and positioning the contribution for a top-tier HPC flagship venue. Use it for strategic venue selection and manuscript re-framing.

This guide provides a comprehensive checklist for auditing experimental rigor in chemical manuscripts, particularly for high-impact journals like JACS. It covers necessary characterization data for new compounds, including NMR, HRMS, elemental analysis, and stereochemistry, and ensures mechanisms and catalytic claims are fully supported by appropriate controls and data.

A comprehensive guide for authors preparing medical manuscripts for high-impact journals. It outlines rigorous standards for statistical reporting, emphasizing the use of effect sizes with 95% Confidence Intervals (CIs) over p-values alone. Key topics include pre-specification, intention-to-treat analysis, multiplicity control, handling missing data through imputation, and reporting both relative and absolute effects to ensure maximum statistical rigor and reproducibility.

This tool acts as a workflow router for preparing clinical manuscripts for high-impact journals like JAMA. It does not replace specialized writing or analysis skills but guides the user through the correct, sequential stages—from initial scope assessment to final submission and revision—ensuring all necessary standards (e.g., EQUATOR, CONSORT) are addressed in the proper order.

A comprehensive guide for structuring and validating empirical research designs (Survey/SEM, Secondary Data, Experiments, Meta-analysis) intended for high-impact journals. It addresses critical methodological issues such as construct validity, endogeneity control, robust identification strategies, and ensuring overall rigor across diverse academic genres.

This skill acts as a comprehensive router for manuscripts aiming at the Journal of the Academy of Marketing Science (JAMS). It guides researchers through the complex, multi-stage process of academic writing—from initial topic selection and theoretical development to data analysis, writing style, and revision strategies (R&R). Use it to diagnose bottlenecks or determine the optimal sequence of specialized marketing science skills needed for high-impact publication.

A comprehensive guide for advanced quantitative research, focusing on demonstrating the validity of econometric methods. It outlines best practices for combining rigorous Monte Carlo simulations (stress-testing DGPs, baselines) with substantive real-world data applications, essential for publication in high-impact economics and statistics journals.

A comprehensive guide for advanced statistical analysis in consumer psychology, moving beyond simple p-values. It details how to rigorously test complex processes like mediation and moderation (measured and experimental). This resource emphasizes reporting standards for high-impact journals, covering effect sizes, confidence intervals, pre-registration, and establishing causal evidence.

This comprehensive guide assists users in analyzing and reporting data for high-impact academic journals, specifically following the rigorous standards of the Journal of Consumer Research (JCR). It covers advanced statistical process evidence (mediation, moderation, effect sizes) for behavioral experiments, as well as methods for establishing trustworthiness in interpretive (CCT) research. It emphasizes transparency, replication code, and adherence to modern research reporting mandates.

A comprehensive guide detailing the advanced statistical standards required for publishing in top educational psychology journals. It covers modeling nested data (multilevel/SEM), reporting educationally meaningful effect sizes with confidence intervals, testing theoretical mechanisms (mediation/moderation), and ensuring full methodological disclosure (JARS). This resource is crucial for researchers aiming for high-impact, reproducible empirical studies.

This comprehensive guide outlines the rigorous methodology required for empirical and theoretical growth studies, particularly for high-impact journals like JEG. It covers best practices for cross-country panel data analysis, calibration techniques, spatial inference (Conley SEs), and structuring robust manuscripts. Use this checklist when estimating growth outcomes, simulating transition paths, or conducting deep sensitivity analyses for development economics.

A comprehensive guide for planning and stress-testing empirical analysis in financial intermediation, specifically for high-impact journals. It covers the construction of bank/loan-level panel datasets, defining variables (growth vs. levels), implementing advanced econometric specifications (e.g., fixed effects), and executing substantial robustness checks (placebo periods, alternative clustering). It also guides the planning of reproducible numerical illustrations for theoretical models.