Skill UI

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 methodological standards for conducting high-impact research in Manufacturing and Service Operations Management. It covers both analytical modeling (proofs, sensitivity) and empirical studies (identification, robustness), emphasizing the necessity of full data and code replicability for published findings.

A guide for developing rigorous analytical or stochastic models for Manufacturing & Service Operations Management (M&SOM). It emphasizes translating operational decisions, objectives, and uncertainties into explicit structural results, such as policy forms (e.g., order-up-to levels) and comparative statics, ensuring the core insight remains operational rather than merely descriptive.

This guide outlines the stringent standards for ensuring the reproducibility of Natural Language Processing (NLP) research. It teaches authors how to treat the Responsible NLP checklist as a binding contract by meticulously 'pinning' every variable—including model identifiers, API access dates, prompt strings, random seeds, and evaluation metrics. It details creating a comprehensive reproducibility manifest to make research results verifiable and defensible.

This comprehensive guide outlines the specific requirements for submitting high-level, synthesis-driven review articles to Nature Reviews Earth & Environment. It details the journal's unique model, which emphasizes comprehensive synthesis, expert adjudication of literature, and setting future research agendas, rather than reporting primary data. The guide covers scope, mandatory structure, and the necessary pre-submission inquiry process.

This guide assists researchers in determining whether a manuscript's topic, methodology, and theoretical contribution are appropriate for a specific theory-building management journal. It provides detailed criteria for evaluating conceptual relationships, suitable methods (SEM, experiment, case study), and appropriate re-routing suggestions for papers that are misaligned with the target journal's scope (e.g., pure math models, macro policy evaluation).

This comprehensive guide provides rigorous methodological rules for developing academic hypotheses. It emphasizes that every hypothesis (main effect, mediation, or moderation) must be justified by an explicit, named theoretical mechanism, moving beyond mere correlation or intuition. Essential for strengthening the theoretical foundation of quantitative research models.

A comprehensive guide for conducting advanced quantitative research using Structural Equation Modeling (SEM) on questionnaire data. It details rigorous procedures for testing complex causal relationships, including mediation, moderation, and moderated mediation, alongside handling nested data via Hierarchical Linear Modeling (HLM). Essential for academic papers requiring robust inference.

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.

A comprehensive guide for authors targeting top-tier security conferences like NDSS. This skill helps determine manuscript fit, refine the academic framing, strengthen evidence, and understand venue-specific expectations (e.g., realistic attacker models, empirical validation). It serves as a strategic tool for conference submission planning, comparing submissions against related venues like USENIX Security and CCS.

Provides comprehensive guidelines for packaging and presenting research artifacts (code, data, models, benchmarks) submitted to NeurIPS. It details requirements for anonymous review packages, public release, and ensures scientific claims are reproducible by providing necessary metadata, licenses, and execution details.

A comprehensive guide for authors submitting to Nature Geoscience. It details the critical distinction between the main article text, online Methods, and Supplementary Information (SI). Learn how to ensure your core findings are stand-alone and decisive, while relegating extensive datasets, model ensembles, and derivations to the SI, maintaining academic rigor and clarity.