Technical Report v1.19.1: The DB-Building Pipeline Behind Technical Reports v1.12–v1.16, Released for Reuse on Any Dataset

This releases, unedited and in its 2026-09-01 state, the exact code pair (`build_notta_tta_comp_db.py` and `heatmap_tool.py`) that generated every number published in Technical Reports v1.12 through v1.16. Anyone who reads the formulas and methods already published in this series could in principle reimplement equivalent code themselves; this release is for those who don't want to spend the effort building it from scratch. It is designed to work with any GT/notta/tta image folder, not just this project's own dataset, so anyone can build the same kind of database and run the same kind of investigation on their own data and models. For example SQL queries against the resulting database, see the other Technical Reports in this series. A recording of the tool actually running is included so it's clear what to expect. The full source is released, including its hardcoded values, so that anyone is free to adapt it to their own use case. CC BY-NC. Dataset and Mandatory Citation:- Source: NIH ChestX-ray8 (Hospital-scale chest x-ray database)- Citation: Wang, X., Peng, Y., Lu, L., Lu, Z., Bagheri, M., & Summers, R. M. (2017). "ChestX-ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thoracic diseases." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 3462–3471. - Download: https://nihcc.app.box.com/v/ChestXray-NIHCC Contact: s.shiny.n.works@gmail.com (individual) /n.mohumohu@merit-metrics.org (Meritcs) Published by Meritcs (https://merit-metrics.org), an independentresearch organization studying image-quality metric reliability.