{
    "types": {
        "row": {
            "filePath": "T[string]",
            "fileName": "T[string]",
            "year": "T[integer]",
            "site": "T[string]",
            "X_Min": "T[float]",
            "Y_Min": "T[float]",
            "X_Max": "T[float]",
            "Y_Max": "T[float]",
            "d_X": "T[float]",
            "d_Y": "T[float]",
            "d_X_cm": "T[float]",
            "d_Y_cm": "T[float]",
            "size": "T[float]",
            "confidence": "T[float]",
            "class": "T[integer]"
        }
    },
    "enums": {},
    "structure": [
        "T[row]"
    ],
    "notes": {
        "id": "biomoth-csv",
        "evidence": "Real author checkpoint on CPU, populated specimen output and empty blank control. See src/probe/reports/2026-09-30-format-expansion/biomoth/report.json for exact invocation and scope. This is a format probe, not an accuracy evaluation.",
        "serialization": "text/csv with header",
        "representation": "One CSV table decoded using the header as field names. Numeric cells may be safely cast to the declared types; the author writes CSV, not JSON objects.",
        "header": [
            "filePath",
            "fileName",
            "year",
            "site",
            "X_Min",
            "Y_Min",
            "X_Max",
            "Y_Max",
            "d_X",
            "d_Y",
            "d_X_cm",
            "d_Y_cm",
            "size",
            "confidence",
            "class"
        ],
        "producer": "runInference.ipynb batch_process",
        "scope": "Active batch export predictions_2023.csv after TorchScript inference, confidence filtering, NMS and undoing letterbox padding. Excludes commented single-image CSV exports and downstream biomass aggregation.",
        "coordinates": "X_Min,Y_Min,X_Max,Y_Max are floating-point original-image pixel corners, clipped to image bounds. d_X and d_Y are pixel width/height.",
        "measurements": "d_X_cm=d_X*(83/6040), d_Y_cm=d_Y*(44/3420); size is their product in square centimetres. These are hard-coded author calibration factors, not calibration for arbitrary images.",
        "identity": "year is hard-coded to 2023; site comes from LOCATIONS; filePath is site/fileName. The single-class branch assigns class 0; float serialization such as 0.0 is safely castable to integer.",
        "confidence": "Detector confidence in [0,1]; notebook defaults CONF_THRES=0.25 and IOU_THRES=0.50.",
        "empty": "Images without retained detections contribute no rows, so the CSV alone cannot distinguish them from unprocessed images. A header is written even when the first image has no detections.",
        "sources": [
            {
                "url": "https://github.com/Suhavi/Lepidoptera_Hubbard_Brook/blob/1d631ce7af4c0fa8eae5d60d8f2ec352fa2644f3/notebooks/runInference.ipynb",
                "revision": "1d631ce7af4c0fa8eae5d60d8f2ec352fa2644f3"
            }
        ],
        "adapters": {
            "import_collection": "iai_model_zoo.formats.adapters.biomoth:import_collection"
        }
    }
}