{
    "action": "final",
    "content": "The query returned 15 rows, 5 from each of the three species (setosa, versicolor, virginica). The rendered block shows them, so this is a balanced sample and not a random draw. Each row is one flower specimen with four measurements in cm: sepal length, sepal width, petal length and petal width.\n\nThe sample already shows the main pattern in the dataset:\n- **Setosa** has small petals. Petal length is about 1.4 to 1.7 and petal width is about 0.1 to 0.3. Its sepals are relatively wide, up to 4.1 in one row.\n- **Versicolor** sits in the middle. Petal length is about 3.3 to 4.5 and petal width is about 1.0 to 1.5.\n- **Virginica** has the largest flowers. Petal length is about 4.9 to 6.7 and petal width is about 1.8 to 2.2.\n\nPetal measurements separate the species more cleanly than sepal measurements do. Sepal length and width overlap between versicolor and virginica. In this sample, one virginica row has petal length 4.9 and sits close to the versicolor range.\n\nThe raw table has 150 rows and also carries ingestion metadata columns (`_ingestion_timestamp`, `_batch_id`, `_source_file`, `_source_system`), which I left out of this sample. I can compute per-species summaries or check feature separation in more detail if you'd like."
}