Skill UI

A highly specialized guide for revising academic econometrics manuscripts for submission to top journals like EctJ. It focuses on extreme conciseness, structural adherence (e.g., 150-word summaries, 20-page limits), and maximizing the impact of core findings over background detail. This skill helps authors transform diffuse research into compact, publishable, and highly focused academic prose.

This guide outlines best practices for achieving high levels of research reproducibility for academic papers, particularly in database and systems research. It details methods for pinning dataset versions, logging system environments, mapping empirical claims to verifiable evidence, and structuring availability statements. Adherence ensures the work is robust, transparent, and fully verifiable by the scientific community.

This comprehensive guide helps researchers audit their papers before submission to the EDBT conference. It covers critical steps including selecting the correct submission cycle and paper shape (Regular, Vision, Experiments & Analysis), adhering to strict formatting standards, managing the 12-month resubmission ban, ensuring double-blind compliance, and providing verifiable, reproducible artifacts. It is essential for academic publishing compliance.

A comprehensive project management guide for submitting database systems papers to EDBT. It details the complexities of the multiple-cycle rolling publication model, covering everything from initial evidence lock and cycle selection to the five-step review arc (Submission, Author Feedback, Revision, etc.). Use this to backward-plan your research timeline and manage the entire academic publishing process.

This skill guides users through strengthening the causal identification strategy of empirical economic manuscripts (DiD, IV, RDD, Experiments). It helps audit research designs against general academic credibility standards, ensuring that assumptions, potential biases, and the link between data variation and causal objects are explicitly stated and robustly defended for diverse expert audiences.

This guide outlines the mandatory structure for creating a reproducible research package, required by academic journals like the European Economic Review (EER). It details how to properly assemble raw data, master analysis scripts, environmental specifications, and comprehensive documentation (README) to ensure that reported results can be independently verified by others. It is essential for any paper involving empirical analysis or simulations.

A comprehensive guide for building a 'robustness battery' to validate empirical findings. It instructs researchers on thoroughly testing results against potential weaknesses in specification, sample selection, measurement, estimator choice, and inference assumptions. Essential for publishing rigorous, credible quantitative research.

This skill provides comprehensive guidance for authors submitting manuscripts to Environment International. It focuses on the rigorous connection between measured environmental exposures (including the exposome, contaminants, and mixtures) and quantifiable, population-relevant human health outcomes or risks. It covers methodology requirements, epidemiological rigor, and journal-specific formatting standards to improve manuscript suitability and reduce desk rejection risk.

This comprehensive guide helps authors determine the suitability and necessary framing for research related to environmental contamination. It mandates moving beyond simple pollutant detection, requiring rigorous evidence to connect contaminants to their fate, transport, and demonstrable ecological or human health impact. Essential for method validation, QA/QC, and scientific rigor.

This guide provides detailed reporting norms for reducing and analyzing complex Earth and Planetary Science Letters (EPSL) data, specifically focusing on isotope geochemistry and geochronology. It mandates full uncertainty budgeting, proper statistical interpretation (e.g., MSWD, weighted means), and thorough model diagnostics to ensure results are scientifically defensible and reproducible.

This guide provides rigorous standards for developing figures and tables in Earth and Planetary Science Letters (EPSL). It emphasizes making complex scientific arguments legible to a cross-disciplinary audience by mandating visible uncertainty (error ellipses, error bars), providing spatial context, and adhering to strict sub-field conventions (e.g., MSWD, depth scales). It teaches how to structure exhibits so that figures carry the argument, while detailed data resides in the supplementary material.

This guide provides best practices for ensuring scientific reproducibility in Earth and Planetary Science Letters (EPSL) manuscripts. It details how to structure supplementary materials, data tables, and analytical code to comply with modern research data policies (FAIR principles). It directs authors on depositing data into recognized community repositories (e.g., PANGAEA, Zenodo, EarthChem), ensuring that the paper's findings can be independently validated by any reader.