Reproducible studies
Papers become recipes, not new code
The platform separates three things. The physical models are the ingredients and the analysis methods are the equipment. A study is a recipe that says which of each to use, in what order and with which data. A recipe never brings its own physics.
A study recipe (.olh2study, versioned JSON) declares:
- sites and datasets, with SHA-256 hashes and the weather years that passed quality control;
- the export pathway, technologies and fidelity levels;
- which components are fixed and which are optimized, with their bounds;
- cost boundaries, optimization settings and seeds;
- experiments, requested outputs and provenance, including what the recipe was cloned from.
Each experiment is shown as Ready, Declared (valid, but not yet connected to a runner) or Blocked (with the reason). Only Ready experiments run, and each run writes to a new folder with a manifest of its inputs and hashes. Generic runners currently execute baseline, sensitivity, uncertainty, interannual and NSGA-II experiments for single-site studies.