Skill UI

This comprehensive guide outlines the standardized procedures and required repositories for ensuring data and code availability in scientific publications, particularly in molecular biology. It details where to deposit various data types (e.g., sequencing, structures, proteomics) in approved archives (GEO, PDB, PRIDE, Zenodo), provides the mandatory standardized statement format, and emphasizes the need to obtain accessions/DOIs before submission to ensure reproducibility.

A comprehensive, step-by-step checklist designed for authors preparing manuscripts for submission to Manufacturing & Service Operations Management (M&SOM). It covers crucial elements including double-anonymous anonymization, strict formatting rules (32-page cap, structured abstract), proper departmental routing, and data/code disclosure requirements, ensuring readiness for the scholarOne portal submission.

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 audit tool designed to ensure academic paper compliance before submitting to major AI conferences like NeurIPS. It systematically checks adherence to the CFP, double-blind anonymity across all assets (PDF, code, data, supplement), correct track selection, and avoids common desk-rejection pitfalls, ensuring the submission is ready for OpenReview.

A comprehensive guide for authors preparing their research paper for the final camera-ready submission at a major academic conference. It details the entire workflow, covering transforming anonymous drafts into public, presented papers. Key steps include de-anonymizing content while adhering to strict page limits, managing public artifact releases (code/data), designating presenters, and meeting critical deadlines for open-access proceedings.

This comprehensive preflight checklist is designed for authors preparing manuscripts for top academic journals. It guides users through crucial submission requirements, including double-blind anonymization, adherence to strict length norms (under 50 pages), structuring the contribution case, and ensuring compliance with modern transparency policies regarding data, code, and AI usage. Use it to maximize submission quality and minimize desk rejection risk.

A comprehensive pre-submission checklist for Operations Research (OR) manuscripts targeting INFORMS/ScholarOne. This guide verifies critical requirements including soft double-anonymous anonymization, contribution statement formatting, page limits, correct area routing, and code/data deposit readiness, ensuring the manuscript meets all standards before final submission.

This guide details the best practices for submitting supplementary material (like full proofs, benchmark data, and source code) for major academic conferences. It instructs authors on strategically placing content to enhance depth while strictly maintaining double-blind anonymity and ensuring perfect consistency between the main paper and its supporting appendices.

Provides comprehensive guidelines for meeting high-level scientific publication standards, detailing the mandatory deposition of raw data (sequences, structures, datasets) and analysis code into approved public repositories. Learn how to obtain persistent identifiers (DOI/Accession) and ensure the reproducibility and integrity of your research findings for journals like PNAS.

This guide outlines the mandatory standards for open science publication, detailing how researchers must deposit all data, code, and raw materials (images, sequences) in public, archived repositories (like Zenodo, GEO, PDB). It emphasizes the need for DOIs/accession numbers and prohibits relying solely on "available on request" statements for primary findings.

This guide outlines the rigorous requirements for preparing a reproducible package for Quantitative Economics (QE) journal submissions. It details the strict standards set by the Econometric Society Data Editor, covering raw data, code, documentation, and handling complex data exemptions to ensure the submission passes the pre-acceptance reproducibility check (DCAS compliant).

This comprehensive guide details the entire editorial review process for quantitative economics publications, covering stages from initial desk screening through to pre-acceptance reproducibility checks. It provides critical insights into expected timelines (4-5 months), desk-reject risks, the Econometrica transfer option, and mandatory data/code preparation requirements. It is designed to set clear professional expectations for authors throughout the academic publishing cycle.