Skill UI

Rowan is a cloud-native workflow platform providing a unified Python API for complex molecular modeling and medicinal chemistry tasks. It handles property prediction (pKa, descriptors), conformational analysis, molecular docking, and molecular dynamics. Users can run scalable, multi-step drug discovery pipelines and batch screening campaigns without managing local high-performance computing infrastructure.

This skill provides a systematic framework for diagnosing and proposing structural repairs for organizational failures. It moves beyond personal blame by analyzing complex dynamics such as team structures, project bottlenecks, authority chains, and governance gaps. It generates actionable memos and low-risk pilot plans, ensuring solutions address systemic root causes rather than individual shortcomings. Best used when CrossFrame Suite routes explicit organizational tasks.

This skill generates a comprehensive, structured guide for planning and facilitating any type of workshop, strategic session, or collaborative meeting. It covers the entire lifecycle, including defining clear objectives, designing detailed activities with instructions, managing group dynamics and conflicts, and ensuring concrete commitments and next steps are captured. Ideal for project managers, trainers, and team leads.

This guide provides rigorous guidelines for creating high-quality figures and tables for complex systems manuscripts, especially in agricultural science. It emphasizes shifting focus from single-factor bar charts to systemic visualizations that reveal interactions, trade-offs (e.g., Pareto fronts), model dynamics, resource flows (Sankey diagrams), and model performance (observed-vs-simulated fit). Exhibits must be self-contained, reproducible, and convey uncertainty.

This guide provides a comprehensive framework for understanding the academic peer review process used at AISTATS, covering everything from OpenReview submission workflows and author-reviewer dynamics to advanced decision criteria (correctness, significance, empirical support). It helps researchers strategize their submissions and responses to maximize acceptance chances in statistics and machine learning.

This guide provides comprehensive methodological frameworks for designing rigorous empirical studies suitable for top-tier academic journals. It helps researchers match theoretical claims (e.g., causal effects, cross-level dynamics) to appropriate designs (experiments, panel data, qualitative analysis). It details how to proactively address major threats like Common-Method Bias, Endogeneity, and inconsistent levels of analysis, ensuring high internal and external validity.

This skill provides a comprehensive pre-submission checklist for manuscripts targeting Atmospheric Chemistry and Physics (ACP), an EGU journal. It details the journal's scope—covering aerosols, clouds, chemistry, and dynamics—and outlines the rigorous standards required, including open-access policies, mandatory FAIR data practices, detailed methodological transparency, and preparation for interactive public peer review. Use this guide to assess the fit and completeness of your scientific work.

This guide provides an in-depth analysis of the CIKM peer review process, which operates under double-blind rules and integrates perspectives from three distinct fields: Information Retrieval, Data Mining, and Knowledge Management. It details how authors can optimize their submissions to satisfy diverse expert standards, how to interpret complex, multi-faceted review reports, and the critical dynamics that determine a paper's acceptance status.

This comprehensive guide outlines the academic standards and best practices for drafting or revising papers in the Computer-Supported Cooperative Work (CSCW) domain. It provides detailed advice on managing effective word count, shifting focus from individual users to group dynamics, strengthening theoretical arguments, and presenting empirical evidence with high academic rigor. Essential for researchers aiming for top-tier publication.

A comprehensive guide detailing the multi-stage academic conference paper review process, such as EMNLP's two-stage pipeline. It covers strategic elements like understanding the difference between Soundness and Excitement scores, optimizing the author response for the Area Chair's meta-review, and managing resubmission dynamics to maximize acceptance chances.

This guide instructs authors on how to craft a robust, cross-disciplinary gap statement for high-level earth science journals. It teaches that a paper's contribution must be framed by triangulating evidence across multiple sub-fields (geochemistry, geophysics, geodynamics, etc.) and competing hypotheses, rather than focusing solely on a single methodological community.

This guide provides rigorous guidelines for designing and presenting results in Experimental Economics manuscripts. It emphasizes making the treatment comparison and its uncertainty immediately visible through specific figure types (distributions, dynamics plots) and structured tables, ensuring the findings are self-contained and highly credible for academic review.