Skill UI

A comprehensive skill designed for authors targeting Classical and Quantum Gravity (CQG). It guides users on the journal's specific scope, methodological rigor (including mathematical proofs, numerical analysis, and observational constraints), and appropriate academic framing for manuscripts in general relativity, cosmology, and quantum gravity. Use this to assess article suitability before submission.

This skill acts as an academic positioning tool for targeting high-level journals focused on institutional and economic comparison, such as the Comparative Economic and Social Systems journal. It helps users assess if their manuscript possesses the necessary comparative scope, institutional logic, and generalizable theoretical contribution required for acceptance, guiding manuscript reframing and submission strategy.

This skill guides authors in assessing the suitability and optimal framing of their machine learning research in the health domain for top-tier academic conferences like CHIL. It ensures the manuscript meets the specific evidence standards, emphasizing clinical grounding, fairness, robustness, and deployment constraints, transforming general CS narratives into specialized health ML contributions.

This tool provides a comprehensive guide to the manuscript review process for Demography journal. It details the double-blind review structure, the mandatory pre-review desk screening (by Editor/Deputy Editor), and the common grounds for desk rejection. By stress-testing your paper against these academic standards, authors can significantly improve their work, ensuring methodological rigor and general interest before submission.

This skill provides a comprehensive framework for assessing whether a research project meets the academic scope of general population science. It guides users to shift focus from mere data usage to advancing core demographic questions concerning fertility, mortality, migration, and population change, helping to frame the contribution for maximum impact.

A comprehensive guide for researchers structuring empirical papers for top-tier economics journals. It covers advanced quasi-experimental techniques (DID, IV, RDD) and structural estimation, emphasizing that successful submissions require not only statistically credible identification but also broad, defensible economic meaning and general relevance. Includes detailed checklists for robustness checks and diagnostic steps.

Provides comprehensive guidelines for authors preparing tables and figures for high-impact economics journals. The core principle is ensuring that every exhibit is self-contained, legible, and communicates the economic magnitude and meaning to a generalist audience, even without reading the surrounding text. It covers best practices for reporting elasticities, confidence bands, and structuring arguments.

This guide assists researchers in structuring and rigorously developing the economic model or mechanism for academic papers. It provides best practices for moving beyond mere empirical findings, ensuring that every result is tied to a clear, testable economic theory, whether through minimal-model discipline or full general equilibrium analysis. Essential for submissions to top-tier economics journals.

A comprehensive pre-submission strategy guide designed to 'red-team' theoretical and econometric manuscripts. This tool helps authors anticipate and pre-empt harsh critiques from expert co-editors and referees, focusing specifically on identifying proof gaps, testing the generality of claims, ensuring finite-sample evidence, and addressing potential methodological competitors before journal submission.

This tool helps researchers diagnose whether their empirical or theoretical result meets the high standards required for top-tier academic journals like Econometrica. It guides users to evaluate the generality, methodological novelty, and theoretical depth of their work, ensuring the contribution is a generalizable estimator or theorem, not merely an application.

This guide offers a rigorous framework for structuring advanced econometric theory papers. It details how to move beyond simple identification by defining minimal, defensible assumptions, proving advanced limit theorems (e.g., FCLT, high-dimensional limits), and ensuring the result's generality across various data regimes (stationary, nonstationary, semiparametric). Use this when theoretical rigor is the primary challenge.

This skill guides researchers on how to position a new econometric theorem by rigorously comparing it against the existing theoretical literature frontier. Instead of a general survey, it requires defining the 'delta'—the specific element (e.g., weaker assumptions, broader scope, generalization) that distinguishes the new result from prior work, using formal APA author-date citations. Essential for high-level academic manuscripts.