Skill UI

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.

This skill provides a comprehensive guide for authors determining the fit of their empirical software engineering (SE) manuscript for the International Symposium on Empirical Software Engineering and Measurement (ESEM). It helps authors rigorously check the study design, evidence bar, proper framing, and necessary re-framing required to transform a journal or arXiv-style paper into a high-quality conference submission suitable for ESEM reviewers. It focuses on measurement validity, experimental rigor, and evidence synthesis.

This tool serves as an expert workflow router for manuscripts targeting top-tier International Relations journals. It guides authors through the entire academic writing process—from initial topic selection and theory building to data analysis, experimental design, and final submission. Its primary function is to ensure the research maintains a strong, generalizable theoretical focus on international or cross-border phenomena, rather than focusing only on domestic case studies.

This guide provides comprehensive guidelines for designing, conducting, and auditing empirical studies in software engineering. It emphasizes achieving scientific rigor by matching every claim to specific, measured evidence, ensuring fair baselining (equal budget), and applying appropriate advanced statistics (non-parametric tests, effect sizes). Essential reading for researchers submitting papers based on performance evaluations.

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 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.

This guide provides comprehensive methodological advice for academic submissions in Information Systems (IS), particularly for journals like JAIS. It covers selecting and rigorously defending diverse research designs—including behavioral experiments, causal inference (Economics of IS), design science, qualitative studies, and literature reviews. Use it when you need to validate the suitability of your methodology against your research claims and underlying phenomena.

A guide for academic researchers to determine if a consumer phenomenon belongs in the Journal of Consumer Psychology (JCP) or a related journal (like JCR or JMR). It helps set the scope, confirm the psychological mechanism, and select the appropriate manuscript type (e.g., Research Report vs. full Article), ensuring the contribution is theory-driven and experimentally testable.

A comprehensive guide for designing and presenting rigorous experiments for submissions to the Journal of Software (JOS). It guides users through setting clear Research Questions (RQ), selecting real-world datasets and baselines, applying advanced statistical testing (effect size, significance), conducting ablation studies, and addressing threats to validity (internal, external, conceptual). This ensures the evidence strongly supports the claims, meeting top-tier academic standards.

This guide provides comprehensive best practices for authors submitting software-related papers to academic journals. It details how to ensure experimental results are fully reproducible and verifiable by peers, covering data/code availability, environment dependency fixing, random seed control, and proper artifact organization for submissions.

This framework guides the creation of mandatory STAR Methods, ensuring scientific manuscripts meet the highest standards of transparency and reproducibility. It mandates the systematic inclusion of Key Resources Tables (KRT), detailed resource availability, experimental model specifications, step-by-step methods, and consolidated statistical analysis (QSA). Ideal for researchers needing to structure complex biological or chemical research findings for publication.

A comprehensive guide detailing the high standards required for presenting security evidence at major conferences. It covers methodologies for proving claims—including attacks, defenses, and detection systems—across live internet measurements, controlled testbeds, and emulation. Key requirements include adaptive adversary modeling, rigorous measurement hygiene, and adherence to ethical review protocols to ensure results are reproducible and relevant to real-world networks.