Skill UI

This guide provides detailed standards for polishing sociological manuscripts, helping authors transition from policy-report tones and overly technical model descriptions to a balanced, scholarly register. It focuses on grounding theoretical arguments in concrete social mechanisms and processes, enhancing the academic depth of the work.

A comprehensive guide for writing the evaluation section of a systems paper for top-tier conferences. It teaches authors how to map every technical claim to verifiable experiments, establish fair state-of-the-art baselines, utilize mixed workloads (microbenchmarks, E2E applications, and traces), and honestly report critical metrics like performance tails, variance, and overheads. The goal is to maximize credibility and withstand rigorous peer review.

This guide provides detailed criteria for submitting theoretical, critical, or interdisciplinary articles to high-level sports science journals. It emphasizes the need for original theoretical contributions, methodological critique, and deep academic dialogue, rather than standard empirical reports or policy recommendations. Ideal for advanced researchers building new conceptual frameworks.

A comprehensive guide for executing and reporting complex social psychological analyses required for expert peer review. This skill covers norms for reporting uncertainty, assessing measurement quality, ensuring robustness checks, selecting appropriate statistical inference (e.g., multilevel models, clustering), and linking statistical findings back to the theoretical structure. It emphasizes methodological rigor and reproducibility.

This tool guides the transformation of academic manuscripts, particularly in the social sciences, from a policy-report or work-summary tone into a rigorous scholarly argument. It helps users replace vague slogans and empty claims with concrete theoretical mechanisms, ensuring the writing maintains a scholarly, restrained, and macro-perspective, and that every paragraph centers on a discernible core proposition.

A comprehensive guide for researchers submitting academic papers, detailing the standards required for scientific reproducibility. It covers fixing experimental environments (toolchains, datasets, hardware), differentiating result sources (simulation vs. physical measurement), statistical reporting best practices, and providing clear guidelines for code and data availability statements.

This comprehensive guide helps authors determine if their cerebrovascular research is a strong fit for the journal Stroke (AHA/ASA). It outlines the specific scope, high evidence standards (e.g., prespecified outcomes, reporting guidelines like CONSORT/STROBE), house style, and detailed submission checklists required for academic publication in stroke and cerebrovascular medicine. It serves as a vital pre-submission feasibility assessment aid.

This comprehensive guide outlines best practices for designing and auditing empirical evaluations of formal verification tools and algorithms. It stresses the use of shared, community-accepted benchmarks, ensuring fair comparison against the strongest baselines with equal resources, meticulous reporting of all metrics, validating results for soundness, and guaranteeing full reproducibility on clean virtual environments.

A comprehensive guide for authors submitting technical papers, detailing methods to ensure that all reported claims, figures, and benchmark numbers can be independently regenerated. This involves creating VM-ready, self-contained artifacts, mapping every claim to a specific script, and defining clear reproducibility levels (Turnkey, Scripted) to satisfy conference requirements.

A comprehensive guide for conducting and reporting rigorous empirical analysis in academic research, particularly in finance and accounting. It covers selecting appropriate estimators (e.g., DiD, 2SLS, RDD), handling fixed effects, ensuring statistical robustness through placebo and alternative testing, and fulfilling strict data-authenticity and code-access requirements required by top-tier journals.

This skill provides a comprehensive guide for authors assessing the fit and framing of metabolic, endocrine, or diabetes research for The Lancet Diabetes & Endocrinology. It outlines the journal's specific requirements, favoring major randomized trials, large prospective cohorts, and population-level epidemiological studies with clear international clinical or policy relevance. It covers method standards, reporting guidelines (CONSORT, STROBE, PRISMA), and official submission checklists. Note: This is a venue-fit aid, not clinical or regulatory advice.

A comprehensive guide for researchers on assessing the suitability of digital health, AI/ML, or health informatics manuscripts for The Lancet Digital Health. It outlines the journal's strict standards for clinical rigor, external validation, reporting guidelines (TRIPOD, CONSORT-AI), and evidence required for publication.