duplicates
duplicates at Beyond Market Intelligence is a file of 2 stories. The newest of them: “Shared baselines across papers keep your research honest and efficient.” and “Reconciling messy names from different data sources? Let AI simplify it.”. Running the same baseline models across two papers is a practical move, but it raises a fair question about duplication. Reconciling two name columns when neither dataset plays by the same rules is a familiar frustration. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work… The list below is every duplicates story on Beyond Market Intelligence, newest first.
Shared baselines across papers keep your research honest and efficient.
Running the same baseline models across two papers is a practical move, but it raises a fair question about duplication. If the RMSE tables match exactly and only the proposed models differ, you are reusing your own work, which is generally acceptable in research. However, journals may view this as redundant publication if not disclosed clearly. Transparency matters here. Disclose the shared baselines in both submissions and cite the other paper. That approach protects your integrity and keeps the focus on your novel contributions.
Reconciling messy names from different data sources? Let AI simplify it.
Reconciling two name columns when neither dataset plays by the same rules is a familiar frustration. You've got "First Last" on one side, "Last, First" on the other, and that's before the misspellings and partial labels like "M&S" versus "Projected M&S." A simple XLOOKUP or INDEX/MATCH key won't cut it when the data itself is inconsistent. Instead, think about building a fuzzy match approach. Use functions like TRIM, SUBSTITUTE, and maybe even a helper column that strips common prefixes or punctuation.