Skill UI

A comprehensive guide detailing the empirical writing style required for EMNLP submissions. It emphasizes scoping claims to specific datasets and languages, ensuring examples are load-bearing, structuring the argument phenomenon-first, and accurately calibrating hedging language based on evidence strength.

This guide meticulously models the rigorous decision-making machinery of top-tier academic conferences, using EuroSys as a detailed example. It covers the two-round submission cycle, the 'Accept/Revise/Reject' outcome logic, double-blind review mechanics, and critical criteria (like deployment plausibility and verifiable fairness) that determine a paper's success. Ideal for researchers and graduate students preparing systems research submissions.

Provides rigorous guidelines for analyzing experimental game data and constructing numerical examples for high-level theoretical journals. Emphasizes that analysis must be tightly linked to theoretical claims, such as matching observed outcomes to predicted equilibria, rather than serving as general causal evidence. Covers session-level clustering, structural fitting, and ensuring computational reproducibility.

This skill guides the rigorous process of building and auditing dense legal footnote apparatus, specifically for Harvard Law Review (HLR) standards. It ensures every proposition is supported by the cited source at the exact page, verifies quote accuracy, and prepares a verifiable source file, making the submission 'pull-ready' for demanding academic review.

This comprehensive guide outlines the necessary theoretical rigor for algorithms and models submitted to top-tier computational journals. It instructs authors on how to formally state mathematical formulations, rigorously prove model validity, establish convergence, and quantify complexity (e.g., approximation ratios, finite termination). It provides specialized paths for exact methods, metaheuristics, and ML-enhanced OR, ensuring that the theoretical advancements fully support and rationalize the experimental findings.

A comprehensive guideline for establishing and documenting the reproducibility of complex sensor-systems artifacts. It covers necessary components such as firmware sources, detailed hardware Bills of Materials (BOMs) and board files, raw sensor traces, ground truth data, and calibrated measurements. Use this guide to ensure that scientific claims can be verified by a competent reader, detailing the exact dependencies on physical equipment and software toolchains.

A guide for authors submitting to theoretical computer science venues (ITCS). It strictly defines what constitutes valid evidence for a mathematical claim, emphasizing that complete proofs are paramount. The guidelines detail how to use worked examples, separating objects, and appropriately scoped computations, while strongly advising against using empirical benchmarks or performance metrics.

This guide provides strict guidelines for authors submitting highly theoretical papers (e.g., to Journal of Economic Theory) regarding computational, numerical, or empirical evidence. It enforces the 'theory-first' principle, ensuring that all quantitative work—including simulations, examples, and counterexamples—must serve to illustrate, test, or deepen the main theoretical contribution, rather than standing as a standalone finding. Key requirements include maintaining reproducibility, keeping examples minimal, and proper structural placement.

Provides comprehensive guidelines for authors submitting to the Journal of Economic Theory (JET). It details mandatory data sharing (Elsevier Option C), ensuring computational reproducibility for numerical examples, and proper declaration of generative AI usage. This playbook helps authors structure their submissions to meet high academic standards of verifiable evidence and transparency.

This guide provides expert advice on structuring the literature review for top-tier finance journals (e.g., JFE). It teaches authors to move beyond simple chronological listing, instead mapping the core academic debates, pinpointing the exact boundaries of the closest existing work, and articulating concrete, theoretically motivated gaps that the new research fills. This is essential for convincing domain experts of novel contribution.

Provides a comprehensive pre-submission checklist for manuscripts targeting the Journal of Marketing (JM). It verifies adherence to strict, evolving academic guidelines, covering double-anonymization, specific formatting (e.g., 50-page limit, Times New Roman), exact statistic reporting, and mandatory inclusion of a Data Availability Statement. Essential for authors preparing for submission via ScholarOne.

Provides comprehensive guidelines for building high-quality, statistically rigorous tables and figures for Journal of Marketing (JM) submissions. It emphasizes adhering to AMA house style, ensuring results display exact p-values, standard errors, and interpretable effect sizes, while strictly managing the 50-page manuscript budget.