Data and code for: A Domain-Organised, Evidence-Graded Review of Applied Quantum Machine Learning

Evidence coding and analysis code for the review “A Domain-Organised, Evidence-Graded Review of Applied Quantum Machine Learning”. The CSV file codes 75 peer-reviewed application studies (Table S1) and 29 randomly sampled validation studies (Table S2) for execution substrate, circuit width, classical baseline, advantage claim, matched classical control, statistical reporting, reproducibility support and evidence tier. Each study is listed with its DOI and, where it appears in the article’s reference list, its reference number. Tables S1 and S2 are also provided as Additional file 1 of the article. reproduce_counts.py recomputes every count and test reported in the paper, and make_figures.py redraws Figures 1 to 4. See README.txt for usage. Version 1.3: README wording updated, a reference-number column added, one author label corrected and Figures 2 and 3 redrawn without in-image titles. The evidence codes and all counts are unchanged from version 1.2.