Skill UI

This skill provides a comprehensive, end-to-end workflow guide for academic journal submissions, specifically tailored for Acta Electronica Sinica (AES). It maps the entire publishing journey—from topic selection and research design to submission, review tracking, revision, and final publication—into a structured timeline. It helps authors manage complex decision points, adhere to strict deadlines (like the 6-month response window), and avoid common pitfalls, ensuring a systematic approach to high-stakes scholarly publishing.

A comprehensive guide for technical authors preparing manuscripts for prestigious Chinese academic journals, specifically targeting the rigorous standards of Acta Electronica Sinica (AES). This skill covers multiple critical areas, including title formatting, structured abstracts, unit usage, formula typesetting, figure/table standards, and rigorous citation guidelines (GB/T 7714). Use this guide to ensure your paper is professionally polished, highly rigorous, and ready for expert review, significantly minimizing formatting deductions and enhancing academic credibility.

This skill guides authors in assessing the suitability of their research concerning agricultural or forest ecosystems for journals focused on land–atmosphere interactions. It emphasizes that the core contribution must be a biophysical process—such as the exchange of energy, water, or carbon—rather than purely agronomic or ecological observations. Use it to re-frame your work to highlight micrometeorological processes and robust flux measurement methodologies.

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 helps researchers rigorously evaluate if their project meets the criteria for a 'systems analysis' in high-impact journals. It teaches how to shift the research focus from single-factor field trials to complex systems questions that analyze interactions, trade-offs, and emergent behaviors across multiple hierarchical levels, such as the farm to the food system. Essential for properly framing scope and article type before submission.

A comprehensive guide for drafting, polishing, and formatting manuscripts in Agricultural Systems (AgSy). This skill ensures the writing is highly readable for a broad systems-science audience, clearly frames the system contribution, and adheres to demanding journal front-matter requirements (e.g., concise abstracts, Highlights, and graphical abstracts). It focuses on strengthening prose and structure, not generating new content.

This skill provides architectural guidance for writing high-level academic history articles, specifically tailored for the American Historical Review (AHR). It helps writers ensure that the narrative development and the core historical argument are seamlessly interwoven, adhering to strict length and scholarly standards. Use it when outlining complex drafts or restructuring material that feels disjointed.

This skill guides authors in evaluating whether their chemical engineering manuscript meets the high standards of the AIChE Journal. It helps authors re-frame application-specific work into generalizable principles, focusing on fundamental scientific advances, rigorous modeling, and comprehensive experimental validation, ensuring the contribution transcends a single process.

This comprehensive guide helps researchers position their academic paper for AISTATS, ensuring maximum novelty and eligibility. It provides detailed advice on comparative analysis, teaching authors how to contrast statistical methods against both modern ML literature (e.g., NeurIPS, ICML) and established statistical theory (e.g., JASA, Annals of Statistics). It covers proper citation of concurrent work, understanding archival status, and structuring the 'Related Work' section to highlight unique technical contributions.

A comprehensive guide for academics submitting AI and statistical research papers. It details how to map every claim (theoretical, algorithmic, or empirical) to verifiable evidence, covering necessary details like datasets, hyperparameters, random seeds, compute resources, and uncertainty estimates. It outlines the standards for achieving high levels of reproducibility, from descriptive to turnkey, ensuring scientific rigor for top-tier conferences.

This guide provides comprehensive best practices for preparing supplementary materials for major academic conferences like AISTATS. It details the proper structure and handling of appendices, mathematical proofs, code archives, and additional data tables, ensuring that the main paper remains fully understandable even if the supplementary material is ignored by reviewers. Essential for publishing high-quality, robust research.

A comprehensive project management guide for the entire academic lifecycle of submitting a paper to a top-tier conference like AISTATS. It maps all crucial milestones—from initial venue fit and evidence freezing to abstract submission, review discussion, and final camera-ready publication—providing backward-planning heuristics and risk assessment to ensure timely and high-quality submissions.