Skill UI

A comprehensive guide detailing how to structure and populate the supplementary material section of technical research papers, especially in NLP and Machine Learning. It distinguishes between load-bearing elements (main text) and audit trails (appendix), covering prompt verbatim, decoding configurations, full result grids, and code anonymization protocols to ensure high reproducibility and academic rigor.

A comprehensive guide for preparing data-availability statements, shareable data, and reproducible code for conservation biology manuscripts. It outlines best practices for using persistent identifiers (like Dryad or Zenodo), masking sensitive species locations, and documenting full research provenance to meet journal standards.

This guide details best practices for enhancing the credibility of academic manuscripts submitted to scholarly journals, particularly addressing code and data availability. It teaches authors how to proactively provide stable links, checksums, comprehensive reproducibility scripts, and clear licensing statements. The focus is on bolstering trustworthiness for single-blind review processes, even when the journal does not mandate formal artifact badges.

This guide outlines the rigorous standards for creating a research replication package required by major academic journals (like The Economic Journal). It details the necessary components—including a comprehensive README, raw data, executable master code, and output logs—to ensure that all figures, tables, and results are fully reproducible by third parties. Crucial for pre-acceptance checks and maintaining academic rigor.

This guide outlines the creation of a complete, verifiable research package for economic policy manuscripts. It ensures that all empirical, experimental, or simulation results are fully reproducible by providing raw data guides, cleaning scripts, analysis code, and a single 'master' script that runs end-to-end. This process is critical for academic acceptance, allowing reviewers and discussants to independently verify every figure, table, and key number reported in the paper.

This guide details the requirements for creating a comprehensive replication package for manuscripts submitted to Econometric Society journals. It ensures full reproducibility of all results, including code, data provenance, and parameter settings, adhering to the journal's Data and Code Availability Policy. Key components include a master script, reproducible data, and detailed documentation.

A comprehensive preflight checklist for authors submitting manuscripts to Econometrica. It details strict guidelines on manuscript length (main body and supplemental material), formatting, anonymization protocols, membership requirements, and adhering to the latest Data and Code Availability Policy. Use this guide before submission to ensure full compliance with the journal's standards.

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.

A comprehensive guide for environmental science manuscripts, detailing the standards required for data reporting and ensuring research reproducibility. It instructs authors on assembling Supporting Information (SI), writing data-availability statements, and depositing raw data, code, and protocols into recognized public repositories (e.g., Zenodo, GenBank).

This package guides researchers on assembling a comprehensive deposit to meet the high standards of Experimental Economics (ESA) journals. It is crucial for academic submissions, ensuring that the materials—including participant instructions, experiment software, raw data, and master analysis code—are complete enough for others to both reproduce the statistical findings and replicate the entire economic experiment.

This guide outlines the mandatory open data and code requirements for publishing in Global Change Biology (GCB). It details that primary and secondary data, along with supporting code/software, must be archived in public, DOI-minting repositories (e.g., Dryad, Zenodo) prior to acceptance. It emphasizes that 'available on request' is not accepted and provides a structured checklist for ensuring reproducibility and proper metadata submission.

This guide assists authors planning to submit to Games and Economic Behavior (GEB) by detailing best practices for data and code sharing. It clarifies that while data deposition is strongly encouraged for reproducibility, it is not a mandatory requirement. It outlines what to prepare, including raw data, analysis scripts, experimental instructions, and proper availability statements.