diff --git a/.gitattributes b/.gitattributes
index 5093538938123574d64a661e635ebf9a3fdc2a76..1bf49805a0be03e59410d82a9cd57b9e03637f21 100644
--- a/.gitattributes
+++ b/.gitattributes
@@ -1,46 +1,7 @@
-*.7z filter=lfs diff=lfs merge=lfs -text
-*.arrow filter=lfs diff=lfs merge=lfs -text
-*.bin filter=lfs diff=lfs merge=lfs -text
-*.bz2 filter=lfs diff=lfs merge=lfs -text
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-*.mlmodel filter=lfs diff=lfs merge=lfs -text
-*.model filter=lfs diff=lfs merge=lfs -text
-*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.tif filter=lfs diff=lfs merge=lfs -text
+*.tiff filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.pdf filter=lfs diff=lfs merge=lfs -text
*.npy filter=lfs diff=lfs merge=lfs -text
*.npz filter=lfs diff=lfs merge=lfs -text
-*.onnx filter=lfs diff=lfs merge=lfs -text
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-*.pickle filter=lfs diff=lfs merge=lfs -text
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-*.pt filter=lfs diff=lfs merge=lfs -text
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-*.rar filter=lfs diff=lfs merge=lfs -text
-*.safetensors filter=lfs diff=lfs merge=lfs -text
-saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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-*tfevents* filter=lfs diff=lfs merge=lfs -text
-assets/primary_rank_change_preview.png filter=lfs diff=lfs merge=lfs -text
-assets/selection_regret_preview.png filter=lfs diff=lfs merge=lfs -text
-assets/task_rank_map_preview.png filter=lfs diff=lfs merge=lfs -text
-paper/manuscript_final.pdf filter=lfs diff=lfs merge=lfs -text
-paper_outputs/figures/fig_selection_regret_scatter.pdf filter=lfs diff=lfs merge=lfs -text
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-assets/supporting_rank_map_final.png filter=lfs diff=lfs merge=lfs -text
-paper/wildfire_fm_evaluation_contracts.pdf filter=lfs diff=lfs merge=lfs -text
diff --git a/.gitignore b/.gitignore
deleted file mode 100644
index fa8debcaf4c6c24650a584d5abb523c4e1e2be13..0000000000000000000000000000000000000000
--- a/.gitignore
+++ /dev/null
@@ -1,6 +0,0 @@
-__pycache__/
-*.py[cod]
-.DS_Store
-.ipynb_checkpoints/
-*.log
-tmp/
diff --git a/CITATION.cff b/CITATION.cff
new file mode 100644
index 0000000000000000000000000000000000000000..7798244dbb89dd7c366d3f8a8a788d8730aeb902
--- /dev/null
+++ b/CITATION.cff
@@ -0,0 +1,10 @@
+cff-version: 1.2.0
+title: "FireWx-FM"
+message: "If you use this repository, please cite the FireWx-FM technical report or model release."
+type: software
+authors:
+ - family-names: Yang
+ given-names: X.
+date-released: 2026-07-02
+repository-code: "https://github.com/yx21e/Wildfire-fm-evaluation-contracts"
+abstract: "A wildfire-specialized gridded reference model for 12-hour active-fire occupancy prediction over the Lower 48 United States."
diff --git a/LICENSE b/LICENSE
index 9663b6210060f0b72e444d3e11a4460912268e9c..2254be1ae04751bd7e7066e977d5fee8de8bbcfd 100644
--- a/LICENSE
+++ b/LICENSE
@@ -1,9 +1,25 @@
-This release is provided for scholarly reproducibility of the associated paper.
+Code in this repository is released for research use under the MIT License.
-Code files are released under the MIT License.
-Paper-output tables, figures, and bundled summary artifacts are released for
-non-commercial research and review use with attribution.
+Copyright (c) 2026 FireWx-FM contributors
-Raw data from NOAA, NASA, LANDFIRE, Wildfire Risk to Communities, LandScan,
-WFIGS, MTBS, and model providers are not redistributed here. Users must obtain
-those data from the original providers and comply with their terms.
+Permission is hereby granted, free of charge, to any person obtaining a copy of
+the code files in this repository and associated documentation files to deal in
+the code without restriction, including without limitation the rights to use,
+copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the
+code, and to permit persons to whom the code is furnished to do so, subject to
+the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the code.
+
+THE CODE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED,
+INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
+PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
+COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
+IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
+CONNECTION WITH THE CODE OR THE USE OR OTHER DEALINGS IN THE CODE.
+
+Raw NOAA, NASA FIRMS, LANDFIRE, Wildfire Risk to Communities, and LandScan
+datasets are not redistributed by this
+repository. Users must obtain source data from original providers and comply
+with the applicable terms.
diff --git a/README.md b/README.md
index 9093f19284c8e10e2e6e3f58a875314927f64337..a0d83dc8f15844abb1c72deb16dfd3961a49d28c 100644
--- a/README.md
+++ b/README.md
@@ -5,422 +5,105 @@ tags:
- geospatial
- weather
- earth-observation
- - foundation-models
- - evaluation
- pytorch
+ - reproducibility
pipeline_tag: image-segmentation
library_name: pytorch
-pretty_name: WildFIRE-FM
+pretty_name: FireWx-FM
---
-
+# FireWx-FM
-
WildFIRE-FM
+FireWx-FM is a wildfire-focused gridded model for 12-hour active-fire occupancy
+prediction over the Lower 48 United States. The released code maps a fixed
+16-channel tensor on a 5 km EPSG:5070 grid to an active-fire occupancy
+probability map.
-
A wildfire-specialized reference backbone for fixed-contract Earth-FM transfer evaluation
+This Hugging Face release is the clean ICLR/technical-report companion package:
+it includes model code, checkpoints, inference utilities, training/cache
+templates, public data-source notes, example outputs, the ICLR manuscript
+source, and the technical report source.
-
Five seeded California regional PyTorch checkpoints, paper-aligned evaluation artifacts, final figure previews, source-data access notes, and a CONUS retraining recipe for 12-hour wildfire occupancy prediction.
+## Contents
-
-
-
-
-
-
-
-
-
-
-
-
-
-
- Read the paper PDF ·
- Download checkpoints ·
- Training/data loader ·
- Custom spatial serving ·
- Load the model ·
- Inspect task-contract results
-
-
-
5 California Seeded Checkpoints · 16-Channel Gridded Input · 12-Hour Occupancy Lead · CONUS Retraining Recipe
-
-
- Why WildFIRE-FM ·
- Release Navigation ·
- Visual Tour ·
- Quick Start ·
- Training Pipeline ·
- Spatial Serving ·
- CONUS Retraining ·
- Integration Handoff ·
- Task Snapshot ·
- Data Sources ·
- How to Cite
-
-
-
-
----
-
-
-
-
-
-## Release Navigation
-
-
-
- |
-
- Read the compiled manuscript that defines the fixed-contract wildfire transfer setting and reports the final results.
- |
-
-
- Access five seeded WildFIRE-FM weights with manifest metadata and SHA-256 hashes for release auditing.
- |
-
-
- Inspect the compact U-Net implementation used to load the released wildfire occupancy backbone.
- |
-
-
- |
-
- Read the original cache builder, tensor assembly, tile sampler, full-map loader, and training loop.
- |
-
-
- Aggregate native grid probabilities to any user-defined polygon granularity.
- |
-
-
- Clone the repository, instantiate the model, load a seeded checkpoint, and run the artifact check.
- |
-
-
- |
-
- View the final-paper task-contract summary for occupancy, spread, retrieval, burned area, smoke, and heat.
- |
-
-
- Use sanitized CSV and JSON summaries that back the public model-card tables and figure previews.
- |
-
-
- Browse final-paper previews for matching-rule sensitivity, selection regret, and task-form ranking changes.
- |
-
-
- |
-
- See the public provider links and roles for HRRR, FIRMS, LANDFIRE, WRC, LandScan, WFIGS, and MTBS.
- |
-
-
-
----
-
-## Why WildFIRE-FM
-
-Wildfire Earth-FM transfer scores depend strongly on the contract used for comparison: task form, metric, matching rule, spatial scope, and head-selection criterion. The paper studies these choices by holding outputs or features fixed and then changing only the evaluation contract.
-
-WildFIRE-FM is the in-region reference model used in those comparisons. It is trained for 12-hour gridded wildfire occupancy on a California 5 km grid, then evaluated under the same task-specific contracts as the transferred Earth-FM backbones.
-
-The released weights are California regional checkpoints, not nationwide-trained weights. For nationwide use, the release includes a CONUS cache and training recipe under `training/NATIONWIDE_RETRAINING.md`.
-
-This Hub repository is model-first. It provides the released weights, model-loading code, compact result summaries, paper previews, and source-data access notes needed to inspect the release boundary before running larger local reproductions.
-
----
-
-## Key Features
-
-- **Wildfire-specialized reference model:** Compact U-Net for 12-hour occupancy prediction on a projected California grid.
-- **Five seeded checkpoints:** Seeds `1`, `7`, `42`, `99`, and `123` are released with manifest hashes.
-- **Fixed-contract artifacts:** Compact summaries cover matching-rule, head-selection, and task-form comparisons from the final paper.
-- **Source-data aware release:** Provider links and data roles are documented for each public resource used by the study.
-- **Compiled paper PDF:** The readable manuscript is available directly from the Hub release.
-- **Paper-aligned previews:** Figure assets summarize selection regret, supporting-task rank changes, and primary-task rank changes.
-
-
-
-
- Reference model for wildfire transfer
- WildFIRE-FM combines regional weather, active-fire supervision, and static fuel, canopy, housing, and population context on the same grid used by the occupancy contract.
- |
-
- Contract-first evaluation artifacts
- The released summaries keep metric roles separate across decision, overlap, ranking, regression, and supporting-task checks.
- |
-
-
-
- Local-data reproducibility path
- Full raw-data reruns use provider-hosted sources and local feature caches. The Hub release documents those inputs and provides lightweight artifact checks.
- |
-
- Final-paper result previews
- The model card highlights the paper's fixed-output, fixed-feature, and task-form findings without requiring manuscript source files.
- |
-
-
-
----
-
-## Visual Tour
-
-
-
-
-
-**Release contents.** The Hub repository is organized around weights, model code, source-data notes, compact artifacts, and final-paper visual previews.
-
-
-
-
-
-**Head-selection regret.** Choosing a lightweight head by a ranking metric can lose decision performance under the same frozen features.
-
-
-
-
-
-**Supporting-task rank map.** Backbone ordering changes across burned area, analog retrieval, smoke PM2.5, and extreme heat task contracts.
-
-
-
-
-
-**Primary-task rank changes.** Primary-task rankings change under fixed matching-rule and task-form choices.
-
----
-
-## At A Glance
-
-| Signal | Release value |
+| Path | Purpose |
|---|---|
-| Core task | 12-hour gridded wildfire occupancy prediction |
-| Released checkpoint region/grid | California regional grid, 5 km, EPSG:5070 |
-| Nationwide path | CONUS cache and training templates in `training/NATIONWIDE_RETRAINING.md` |
-| Input channels | 16 channels: weather fields, validity masks, static fuel/canopy/exposure layers |
-| Architecture | Compact U-Net with occupancy and auxiliary spatial-support heads |
-| Training split | June-August 2024 train, September 2024 validation, October 2024 test |
-| Released checkpoints | 5 seeded PyTorch checkpoints |
-| Data access path | Source links and roles documented in `data_sources/` |
-| Training/data loader path | Original cache builder and PyTorch loader in `training/` |
-| Spatial serving path | Custom polygon-granularity aggregation in `spatial_serving/` |
-| Paper artifact path | Compiled PDF in `paper/`; manuscript source managed in the authors' paper workspace |
-
-### Input Channel Contract
-
-The pretrained checkpoints expect a fixed 16-channel tensor in `[channel, y, x]`
-order. Channel order matters.
-Inputs use native source units with no mean/std normalization, min/max scaling,
-or unit conversion. Invalid or missing values are zero-filled, with validity
-masks included as channels 10 and 11.
-
-| Channels | Names | Source |
-|---:|---|---|
-| 0-9 | `t2m`, `d2m`, `u10`, `v10`, `cape`, `sp`, `blh`, `vis`, `prate`, `tp` | NOAA HRRR |
-| 10 | `firewx_valid` | Cache-level dynamic input presence mask; 1.0 everywhere in this release |
-| 11 | `static_valid` | Fraction of static layers valid after reprojection |
-| 12-15 | `fuel_fbfm40`, `canopy_cover`, `housing_density`, `population` | LANDFIRE, WRC housing density, LandScan |
-
-FIRMS provides the occupancy target, not an input channel. WFIGS and MTBS are
-used for supporting event-level tasks and are not part of the 16-channel
-pretrained occupancy input. Full channel-level details are in
-`data_sources/DATA_SOURCES.md`; the same contract is available as
-`models/wildfire_fm/input_channels.json`.
-The `cape` channel is the HRRR surface instantaneous CAPE field selected with
-`typeOfLevel=surface` and `stepType=instant`.
-For validity channels, `firewx_valid` is 1.0 everywhere in the released
-California regional cache and is not a per-variable HRRR missing-data mask;
-`static_valid` is the fraction of the four static layers valid after
-reprojection at each grid cell.
-
----
-
-## Hugging Face Release
-
-This Hub repository is a model release with paper-aligned reproducibility artifacts.
-
-| Folder | Purpose | Example |
-|---|---|---|
-| `models/wildfire_fm/` | Model code, manifests, checkpoint metadata | `models/wildfire_fm/modeling_unet.py` |
-| `models/wildfire_fm/input_channels.json` | Machine-readable 16-channel input contract | `models/wildfire_fm/input_channels.json` |
-| `models/wildfire_fm/checkpoints/` | Five seeded PyTorch checkpoints | `seed_1/best_firms_prauc.pt` |
-| `training/` | Original cache builder, data loader, tile sampler, and training loop | `train_cold_tiled_mainline.py` |
-| `training/NATIONWIDE_RETRAINING.md` | CONUS retraining recipe and data coverage notes | `stage1_cache_conus_hrrr_us_5km_l12_template.json` |
-| `spatial_serving/` | Grid-to-polygon serving adapter for custom spatial granularities | `grid_to_polygons.py` |
-| `data_downloader/hrrr_downloader.py` | Direct NOAA HRRR public archive downloader | `hrrr_download_manifest.json` |
-| `docs/hugh_handoff_status.md` | Integration answers for channel order, masks, normalization, HRRR, and serving boundary | handoff status |
-| `paper/` | Compiled paper PDF | `wildfire_fm_evaluation_contracts.pdf` |
-| `assets/` | Hub-page visuals and final-paper previews | `selection_regret_final.png` |
-| `paper_outputs/figures/` | Selected final-paper figure PDFs | `fig_rank_heatmap1.pdf` |
-| `artifacts/results/` | Sanitized compact numeric summaries | `selection_regret_scope_sweep_20260505.csv` |
-| `data_sources/` | Public data-source roles and access notes | `DATA_SOURCES.md` |
-| `experiments/` | Sanitized raw-rerun references and Slurm template | `slurm/submit_template.sbatch` |
-
-Full local reruns require users to prepare the provider-hosted raw data and comparator assets described in `data_sources/`.
-
----
+| `firewxfm/` | Model definition and tiled CONUS inference code. |
+| `models/checkpoints/` | Released PyTorch checkpoints. |
+| `models/metadata/` | Input-channel contract, normalization statistics, and run metadata. |
+| `training/` | Cache-building, training, and metric utilities. |
+| `training/configs/` | Path-free templates for CONUS and multi-year reruns. |
+| `scripts/` | Data preparation, release checks, live-stack builder, seam audit, and smoke tests. |
+| `examples/final_prediction/` | Small final probability/preview example for inspection. |
+| `data_sources/` | Source-data provenance and access notes. |
+| `paper/iclr_source/` | ICLR manuscript LaTeX source. |
+| `technical_report/source/` | Technical report LaTeX source. |
+| `artifacts/results/` | Compact public result summaries without internal filesystem paths. |
## Quick Start
-Clone the Hub repository or download the files you need:
-
```bash
-git clone https://huggingface.co/RAI-Lab/Wildfire-FM
-cd Wildfire-FM
+python3 -m venv .venv
+source .venv/bin/activate
+pip install -r requirements.txt
+python3 scripts/check_release_files.py
+python3 scripts/smoke_inference.py --device cpu
```
-Load a seeded checkpoint:
+The smoke test uses a synthetic tensor. Full scientific reproduction requires
+the public source datasets listed in `data_sources/DATA_SOURCES.md`.
-```python
-import torch
-from models.wildfire_fm.modeling_unet import UNetSmallFlex
+## Model Input Contract
-model = UNetSmallFlex(
- in_ch=16,
- base=32,
- dropout=0.1,
- norm_type="group",
- norm_groups=8,
- use_aux_spatial_head=True,
-)
-checkpoint = torch.load(
- "models/wildfire_fm/checkpoints/seed_1/best_firms_prauc.pt",
- map_location="cpu",
-)
-state = checkpoint.get("model", checkpoint)
-model.load_state_dict(state)
-model.eval()
-```
+The model expects a channel-first tensor with shape `[16,H,W]`.
-Verify the public release artifacts:
-
-```bash
-python3 scripts/reproduce_paper_outputs.py
-```
-
-The checkpoint expects the same fixed-order 16-channel gridded input described
-above and in `data_sources/DATA_SOURCES.md`.
-
----
-
-## Task-Contract Snapshot
-
-The card below reports the best final-paper mean for each displayed task contract, with the winning backbone named in the final column.
-
-| Task contract | Best final-paper mean | Winner |
-|---|---:|---|
-| Occupancy union F1 | `60.1506 ± 7.5865` percent | ClimaX |
-| Fire-spread spatial F1 | `80.9700 ± 2.0200` percent | WildFIRE-FM |
-| Final burned-area log-RMSE | `1.1657 ± 0.0126`, lower is better | WildFIRE-FM |
-| Analog retrieval nDCG@10 | `0.5099 ± 0.0336` | WildFIRE-FM |
-| Smoke PM2.5 RMSE | `4.4403 ± 0.0488`, lower is better | AlphaEarth |
-| Extreme-heat RMSE-C | `0.2179 ± 0.0043`, lower is better | WildFIRE-FM |
-
-The release provides sanitized CSV/JSON summaries used to audit displayed values.
+| Channels | Source | Role |
+|---:|---|---|
+| 0-9 | NOAA HRRR | Dynamic weather fields. |
+| 10-11 | Input builder | Dynamic and static validity masks. |
+| 12 | LANDFIRE | Fire-behavior fuel model. |
+| 13 | LANDFIRE | Canopy cover. |
+| 14-15 | WRC / LandScan | Housing density and population; zeroed in the no-exposure serving run. |
----
+See `models/metadata/input_channels.json` and
+`models/metadata/input_normalization_stats.json` for the exact machine-readable
+contract.
-## Data Sources
+## Inference
-The study uses public or provider-hosted resources. Source roles and access paths are documented in `data_sources/DATA_SOURCES.md`.
+Run inference from a prebuilt 16-channel stack:
-- NOAA HRRR fields for regional weather inputs.
-- NASA FIRMS active-fire detections for occupancy supervision.
-- LANDFIRE fuel and canopy layers for static landscape context.
-- Wildfire Risk to Communities housing density and LandScan population for exposure context.
-- WFIGS and MTBS event-level resources for burned-area and analog tasks.
-- External Earth-FM and backbone assets for comparator features.
+```bash
+python3 -m firewxfm.serve_conus \
+ --input-npy /path/to/input_stack_16chw.npy \
+ --checkpoint models/checkpoints/firewxfm_2024_staticfix_region_balanced_bce_seed42.pt \
+ --normalization-stats models/metadata/input_normalization_stats.json \
+ --output-npy outputs/firewxfm_probability.npy
+```
----
+For full-map serving, use overlap-window inference with phase averaging. The
+default settings are documented in `docs/serving_notes.md`.
-## Repository Layout
+## Reproducibility
-```text
-WildFIRE-FM/
- README.md
- LICENSE
- requirements.txt
- models/wildfire_fm/
- modeling_unet.py
- checkpoint_manifest.json
- checkpoints/seed_*/best_firms_prauc.pt
- training/
- build_phase1_cache_regional_hrrr.py
- train_cold_tiled_mainline.py
- configs/
- spatial_serving/
- grid_to_polygons.py
- data_downloader/
- hrrr_downloader.py
- paper/
- wildfire_fm_evaluation_contracts.pdf
- assets/
- wildfire_fm_model_card.svg
- release_contents.svg
- selection_regret_final.png
- supporting_rank_map_final.png
- primary_rank_change_final.png
- paper_outputs/figures/
- matching.pdf
- fig_task_contract_tiles.pdf
- fig_selection_regret_scatter.pdf
- fig_rank_heatmap1.pdf
- artifacts/
- manifests/
- results/
- data_sources/
- DATA_SOURCES.md
- experiments/
- raw_reference/
- slurm/
- scripts/
- audit_release.py
- reproduce_paper_outputs.py
-```
+Use `REPRODUCIBILITY.md` for the exact verification path:
----
+- artifact presence check,
+- checkpoint smoke inference,
+- ICLR source compilation,
+- technical report source compilation,
+- real-data cache rebuild and retraining commands.
-## How To Cite
+Raw source data are not redistributed. This package documents where each source
+comes from and provides path-free templates for local reproduction.
-If you use WildFIRE-FM, the released checkpoints, the fixed-contract evaluation artifacts, or the paper-aligned scripts, please cite:
+## Citation
```bibtex
-@misc{wildfire_fm_evaluation_contracts_2026,
- title = {Does Your Wildfire Prediction Model Actually Work, or Just Score Well?},
- author = {Yangshuang Xu and Yuyang Dai and Liling Chang and Qi Wang and Yushun Dong},
+@misc{firewxfm2026,
+ title = {FireWx-FM: A Wildfire Foundation Model Technical Report},
+ author = {Xu, Yangshuang and Dai, Yuyang and Chang, Liling and Wang, Qi and Dong, Yushun},
year = {2026},
- note = {WildFIRE-FM model and fixed-contract wildfire evaluation artifacts}
+ note = {FireWx-FM code, checkpoints, and reproducibility package}
}
```
-
-The citation will be updated with arXiv metadata after the preprint is public.
-
----
-
-## News
-
-- **2026-05-18** - The model card was reorganized with a larger navigation panel and final-paper visual previews.
-- **2026-05-13** - The Hub release added the compiled paper PDF without checklist pages.
-- **2026-05-13** - Five seeded WildFIRE-FM checkpoints were uploaded with SHA-256 metadata.
-
----
-
-## Scope
-
-WildFIRE-FM is scoped to the paper's California regional grid and fixed-contract wildfire transfer comparisons. Use in a new region or grid should start with local preprocessing, validation, and contract-specific evaluation. The release is designed for research inspection, artifact-level checking, and model-loading experiments rather than operational alerting.
-
----
-
-## License
-
-This release is provided under the MIT license. External data and comparator assets remain governed by their original providers and terms of use.
-
----
-
-WildFIRE-FM is released to make wildfire Earth-FM transfer comparisons easier to inspect, reproduce at the artifact level, and evaluate under explicit contracts.
diff --git a/REPRODUCIBILITY.md b/REPRODUCIBILITY.md
new file mode 100644
index 0000000000000000000000000000000000000000..7447b40587fc0ff318b9a5104109c258c51f97dc
--- /dev/null
+++ b/REPRODUCIBILITY.md
@@ -0,0 +1,102 @@
+# Reproducibility
+
+This release is designed to make the FireWx-FM technical report and ICLR
+manuscript inspectable and reproducible from documented ingredients.
+
+## What Is Included
+
+- Model and inference code in `firewxfm/`.
+- Training, cache-building, and metric utilities in `training/`.
+- Public-data preparation and audit scripts in `scripts/`.
+- Two released PyTorch checkpoints in `models/checkpoints/`.
+- Input-channel metadata, normalization statistics, and run summaries in
+ `models/metadata/`.
+- A small final prediction example in `examples/final_prediction/`.
+- ICLR manuscript source in `paper/iclr_source/`.
+- Technical report source in `technical_report/source/`.
+- Source-data notes in `data_sources/DATA_SOURCES.md`.
+
+## What Is Not Included
+
+Raw HRRR, FIRMS, LANDFIRE, Wildfire Risk to Communities, LandScan, WFIGS, and
+MTBS data are not redistributed. Users must download those data from the
+original providers and follow their licenses.
+
+## Quick Verification
+
+Install dependencies:
+
+```bash
+python3 -m venv .venv
+source .venv/bin/activate
+pip install -r requirements.txt
+```
+
+Check that required artifacts are present:
+
+```bash
+python3 scripts/check_release_files.py
+```
+
+Verify checkpoint/model compatibility with a synthetic tensor:
+
+```bash
+python3 scripts/smoke_inference.py \
+ --checkpoint models/checkpoints/firewxfm_2024_staticfix_region_balanced_bce_seed42.pt \
+ --device cpu
+```
+
+Compile the technical report source:
+
+```bash
+cd technical_report/source
+tectonic main.tex
+```
+
+Compile the ICLR manuscript source:
+
+```bash
+cd paper/iclr_source
+tectonic main.tex
+```
+
+## Inference From A Real 16-Channel Stack
+
+After constructing a `[16,H,W]` stack that follows
+`models/metadata/input_channels.json`, run:
+
+```bash
+python3 -m firewxfm.serve_conus \
+ --input-npy /path/to/input_stack_16chw.npy \
+ --checkpoint models/checkpoints/firewxfm_2024_staticfix_region_balanced_bce_seed42.pt \
+ --normalization-stats models/metadata/input_normalization_stats.json \
+ --output-npy outputs/firewxfm_probability.npy
+```
+
+The output is an `[H,W]` probability map for 12-hour active-fire occupancy.
+
+## Rebuilding Training Caches
+
+Use the template configs under `training/configs/` after replacing placeholder
+paths with local source-data paths:
+
+```bash
+python3 scripts/prepare_firms_target_hour_csvs.py \
+ --daily-dir /path/to/firms_daily_csv \
+ --output-dir /path/to/firms_target_hour_csv \
+ --config training/configs/stage1_cache_conus_multiyear_template.json
+
+python3 scripts/audit_firewxfm_phase0.py \
+ --config training/configs/stage1_cache_conus_multiyear_template.json \
+ --output artifacts/manifests/phase0_data_split_audit.json
+
+python3 training/build_phase1_cache_regional_hrrr.py \
+ --config training/configs/stage1_cache_conus_multiyear_template.json
+
+python3 training/train_cold_tiled_mainline.py \
+ --config training/configs/train_firewxfm_conus_multiyear_template.json \
+ --run-name firewxfm_conus_multiyear_noexposure_seed42
+```
+
+Large cache building and training should be run on compute nodes, not login
+nodes.
diff --git a/artifacts/manifests/paper_outputs.sha256 b/artifacts/manifests/paper_outputs.sha256
deleted file mode 100644
index 8c0cf0ab9a60e74dc19ec2d35d0e65741f65cc1e..0000000000000000000000000000000000000000
--- a/artifacts/manifests/paper_outputs.sha256
+++ /dev/null
@@ -1,15 +0,0 @@
-6db4f4aff90da8709edff97e4782aee9b4c5e8feefec7c7431a4ec8787cfe57c assets/overview_final.png
-ca11c75c03078a9be26421b527ab5a49f5fc43ce8e5edd7da14af120a247b67c assets/primary_rank_change_final.png
-1f992d7245b55b8674c00753efbd0e25f4e3be658e736b353772624dea2b7a8f assets/release_contents.svg
-5552fb6cca6a0a683592e724b4bd562f923cf99c04e2abdb846546b1d67aecc4 assets/selection_regret_final.png
-34807e65ca71365a26a3b74cae70e6b40ae6f2151110e12c53e0efa9f8b726aa assets/supporting_rank_map_final.png
-7adb6a949bce3203b6cb10a458e115c60ba0b3efdb10f2ca1a1fd508924bc2ac assets/wildfire_fm_model_card.svg
-95596f05829639ecb3041721fe3c871caacc49f30c831d35f2c503b1073b498d paper/wildfire_fm_evaluation_contracts.pdf
-b369d13e0419fa8272ccdc994b6642f3b141248a879c030218e387c583537eb2 paper_outputs/figures/fig_fireprone_contract_progression_compact.pdf
-e3110c70c3cf8ecb8671163a401a155920266e3f907f9c6baf08e27ec6e6c410 paper_outputs/figures/fig_primary_rank_change_map.pdf
-4e5b791ba4d136f722bd75a61097203836819ce9411def1caac4cc1e6d881275 paper_outputs/figures/fig_rank_heatmap1.pdf
-fabb8b55aac901199cc03773741a26685becffd074f52568c93bee517c2c42c0 paper_outputs/figures/fig_selection_regret_scatter.pdf
-bc4d35ad9cb4c1f9ba8f31c7c340d9684c9dd2d55f5a2e60604a2b58b90cbe40 paper_outputs/figures/fig_task_contract_tiles.pdf
-c382f5d69f25cc2f5db174601a33d0fd0928b44910a2a4b1c131954bd42113d9 paper_outputs/figures/fig_task_rank_map.pdf
-015ab951b0af5c130e4894092a5dd0bb0fd62e710467163a9df8246d8cf369f4 paper_outputs/figures/matching.pdf
-7dca6ae4a9b179693802f47d24dd66734c0f332b372a7976832a0d429333b755 paper_outputs/figures/overview_wildfire.pdf
diff --git a/artifacts/manifests/paper_outputs.yml b/artifacts/manifests/paper_outputs.yml
deleted file mode 100644
index 1a7596293669fdaff2dff4b6b02597e49e3b8cd7..0000000000000000000000000000000000000000
--- a/artifacts/manifests/paper_outputs.yml
+++ /dev/null
@@ -1,32 +0,0 @@
-# Auto-generated public-output manifest for the Hugging Face release.
-outputs:
- - path: assets/overview_final.png
- sha256: 6db4f4aff90da8709edff97e4782aee9b4c5e8feefec7c7431a4ec8787cfe57c
- - path: assets/primary_rank_change_final.png
- sha256: ca11c75c03078a9be26421b527ab5a49f5fc43ce8e5edd7da14af120a247b67c
- - path: assets/release_contents.svg
- sha256: 1f992d7245b55b8674c00753efbd0e25f4e3be658e736b353772624dea2b7a8f
- - path: assets/selection_regret_final.png
- sha256: 5552fb6cca6a0a683592e724b4bd562f923cf99c04e2abdb846546b1d67aecc4
- - path: assets/supporting_rank_map_final.png
- sha256: 34807e65ca71365a26a3b74cae70e6b40ae6f2151110e12c53e0efa9f8b726aa
- - path: assets/wildfire_fm_model_card.svg
- sha256: 7adb6a949bce3203b6cb10a458e115c60ba0b3efdb10f2ca1a1fd508924bc2ac
- - path: paper/wildfire_fm_evaluation_contracts.pdf
- sha256: 95596f05829639ecb3041721fe3c871caacc49f30c831d35f2c503b1073b498d
- - path: paper_outputs/figures/fig_fireprone_contract_progression_compact.pdf
- sha256: b369d13e0419fa8272ccdc994b6642f3b141248a879c030218e387c583537eb2
- - path: paper_outputs/figures/fig_primary_rank_change_map.pdf
- sha256: e3110c70c3cf8ecb8671163a401a155920266e3f907f9c6baf08e27ec6e6c410
- - path: paper_outputs/figures/fig_rank_heatmap1.pdf
- sha256: 4e5b791ba4d136f722bd75a61097203836819ce9411def1caac4cc1e6d881275
- - path: paper_outputs/figures/fig_selection_regret_scatter.pdf
- sha256: fabb8b55aac901199cc03773741a26685becffd074f52568c93bee517c2c42c0
- - path: paper_outputs/figures/fig_task_contract_tiles.pdf
- sha256: bc4d35ad9cb4c1f9ba8f31c7c340d9684c9dd2d55f5a2e60604a2b58b90cbe40
- - path: paper_outputs/figures/fig_task_rank_map.pdf
- sha256: c382f5d69f25cc2f5db174601a33d0fd0928b44910a2a4b1c131954bd42113d9
- - path: paper_outputs/figures/matching.pdf
- sha256: 015ab951b0af5c130e4894092a5dd0bb0fd62e710467163a9df8246d8cf369f4
- - path: paper_outputs/figures/overview_wildfire.pdf
- sha256: 7dca6ae4a9b179693802f47d24dd66734c0f332b372a7976832a0d429333b755
diff --git a/artifacts/results/downstream_summary.md b/artifacts/results/downstream_summary.md
new file mode 100644
index 0000000000000000000000000000000000000000..05b2aabf1f2570b80176c1feb65975c63fccd7bd
--- /dev/null
+++ b/artifacts/results/downstream_summary.md
@@ -0,0 +1,26 @@
+# Forced Mean/Std Gap-Fill Summary
+
+## table2_headcontrol
+
+
+## table3_occupancy
+
+
+## table3_spread
+
+- Prithvi-WxC: strict_f1 20.72 +/- 3.80 (n=5); spatial_f1 57.32 +/- 2.14 (n=5); ap 5.04 +/- 0.40 (n=5)
+- Reference: strict_f1 20.32 +/- 1.15 (n=5); spatial_f1 68.58 +/- 1.98 (n=5); ap 30.44 +/- 1.81 (n=5)
+
+## table4_final_area
+
+- Reference: log_rmse 1.17 +/- 0.01 (n=5); log_mae 1.05 +/- 0.01 (n=5); log_spearman 0.59 +/- 0.03 (n=5)
+
+## table4_analog
+
+- reference_strict: ndcg_at_10 0.52 +/- 0.00 (n=5); log_rmse 1.18 +/- 0.00 (n=5); log_mae 0.97 +/- 0.00 (n=5)
+
+## table4_smoke
+
+
+## table4_heat
+
diff --git a/artifacts/results/fireprone_contract_progression_summary.json b/artifacts/results/fireprone_contract_progression_summary.json
deleted file mode 100644
index 2099b6eadc0cc63bf2ddbd793ffc683434dc98e8..0000000000000000000000000000000000000000
--- a/artifacts/results/fireprone_contract_progression_summary.json
+++ /dev/null
@@ -1,16543 +0,0 @@
-{
- "run_roots": [
- "",
- ""
- ],
- "repair_run_roots": [],
- "repair_sources": [
- "",
- "",
- ""
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- "train_fire_top02pct"
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- "repair_threshold_max_ppr": 0.999999,
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