# Split Design For FireWx-FM Refinement This document defines the split logic needed to make FireWx-FM harder to criticize as a regional or autocorrelated supervised model. ## Required Split Families ### 1. Chronological CONUS Split Purpose: test future-season performance across the Lower 48. Recommended default: - Train: 2021-2024 fire seasons. - Validation: 2025 fire season. - Test: 2026 fire season or latest available held-out year. Config support: - Use `split_years` in `stage1_cache_conus_multiyear_template.json`. ### 2. Region-Disjoint Split Purpose: test whether the model transfers beyond the regions it saw during training. Recommended holdout regions: - California / Pacific Coast. - Pacific Northwest. - Rockies / Intermountain West. - Southeast including Florida. - Great Plains / Central. Implementation note: - Masked evaluation can be done with trained full-CONUS checkpoints. - Strict region-disjoint training requires region masks inside the training tile sampler so positive and negative crops from the held-out region are excluded. ### 3. Spatial Block Split Purpose: reduce local grid-cell autocorrelation. Recommended design: - Divide the Lower 48 grid into large projected blocks. - Hold out non-adjacent blocks for testing. - Add buffer blocks between train and test when data volume permits. ### 4. Seasonal Robustness Split Purpose: test whether the model only fits one seasonal window. Recommended designs: - Train early season and test late season. - Train excluding October-like months and test October-like months. - Report monthly positive rate and metric curves. ## Reporting Requirements Every experiment should save: - Config path and SHA-256. - Cache manifest path and SHA-256. - Split rule name. - Number of samples per split. - Number of positive cells per split. - Total FIRMS fire points per split. - Date range per split. - Region mask used, if any. ## Claim Boundary Do not claim broad foundation-model generalization unless both cross-year and region-disjoint tests are reported. A chronological split alone is not enough.