{
    "action": "final",
    "content": "The dataset has one table, `raw.iris`, with 150 rows and 9 columns. The types and roles below come from the dataset card. The species-level figures come from the `iris_by_species` gold table I queried.\n\n**Measurement columns (DOUBLE, all in the same unit, presumably centimetres)**\n- `sepal_length`: length of the sepal, the outer leaf-like part of the flower. Species averages run from about 5.0 (setosa) to 6.6 (virginica).\n- `sepal_width`: width of the sepal. Averages run from about 2.77 (versicolor) to 3.43 (setosa), so this is the least ordered of the four measures across species.\n- `petal_length`: length of the petal. Averages are about 1.46 (setosa), 4.26 (versicolor) and 5.55 (virginica). This is the strongest separator: setosa's range (1.0–1.9) does not overlap the others (3.0 and up).\n- `petal_width`: width of the petal. Averages are about 0.25 (setosa), 1.33 (versicolor) and 2.03 (virginica).\n\nThe card lists these four as the dataset's measures. The unit is not stated in the metadata, so centimetres is an assumption from the standard Iris dataset.\n\n**Classifier column (VARCHAR)**\n- `species`: the class label, with three values (setosa, versicolor, virginica) and 50 specimens each.\n\n**Ingestion metadata columns (added by the pipeline, not flower measurements)**\n- `_ingestion_timestamp` (TIMESTAMP): when the row was loaded.\n- `_batch_id` (VARCHAR): identifier of the load batch.\n- `_source_file` (VARCHAR): the file the row came from.\n- `_source_system` (VARCHAR): the system that supplied the data.\n\nThe descriptions of the four ingestion columns are inferred from their names and the card's temporal note. I did not profile their values."
}