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"model_name": "FireCubeNet",
"model_type": "firecubenet",
"architectures": ["FireCubeNet"],
"framework": "PyTorch",
"domain": "earth-science",
"task": "next-day-wildfire-danger-classification",
"implementation": {
"entry_point": "model/firecubenet.py",
"scope": "paper-task and real-input-dimension scaled engineering reproduction",
"train_script": "scripts/train.py",
"inference_script": "scripts/inference.py",
"evaluation_script": "scripts/result.py",
"synthetic_data_script": "scripts/fake_data.py"
},
"architecture": {
"family": "ConvLSTM center-pixel binary classifier",
"input_layout": "BTCHW",
"input_channels": 25,
"sequence_days": 10,
"patch_height": 25,
"patch_width": 25,
"engineering_hidden_channels": 4,
"loss": "BCEWithLogitsLoss"
},
"data": {
"protocol": "wildfire_danger_spatiotemporal_v1",
"format": "NPZ",
"resolution_km": 1,
"sample_interval_days": 1,
"input_shape": ["B", 10, 25, 25, 25],
"target_shape": ["B", 1],
"channels": [
"maximum_2m_temperature", "maximum_wind_speed", "minimum_relative_humidity",
"total_precipitation", "maximum_2m_dewpoint_temperature", "maximum_surface_pressure",
"ndvi", "day_lst", "night_lst", "soil_moisture_index", "road_distance",
"waterway_distance", "population_density", "elevation", "slope",
"land_cover_fraction_1", "land_cover_fraction_2", "land_cover_fraction_3",
"land_cover_fraction_4", "land_cover_fraction_5", "land_cover_fraction_6",
"land_cover_fraction_7", "land_cover_fraction_8", "land_cover_fraction_9",
"land_cover_fraction_10"
],
"target": "center pixel belongs to a greater-than-30-ha fire starting next day"
},
"configuration_sources": [
"conf/config.yaml", "model/firecubenet.py", "scripts/fake_data.py",
"scripts/train.py", "scripts/inference.py", "scripts/result.py"
]
}
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