# Evaluation anatomy

A useful reference for what an evaluation actually contains, end-to-end.

## At creation

| Field                          | Required                  | Description                       |
| ------------------------------ | ------------------------- | --------------------------------- |
| `name`                         | yes                       | Human-readable name               |
| `model_id` or `model`          | yes (if not a comparison) | The model under test              |
| `benchmark_id` or `dataset_id` | yes                       | The data                          |
| `scorers`                      | optional                  | List of scorer IDs                |
| `judges`                       | optional                  | List of judge IDs                 |
| `tags`                         | optional                  | For filtering and audit           |
| `parent_run_id`                | optional                  | Link to the previous baseline run |

## During execution

States: `queued` → `running` → `completed` (or `failed`, `cancelled`).

Per-row work:

1. Construct the prompt from the dataset row
2. Call the model
3. Apply each scorer to the (input, output, expected)
4. Apply each judge to the (input, output)
5. Record the row's verdicts, latency, cost

## At completion

| Field                        | Description                               |
| ---------------------------- | ----------------------------------------- |
| `id`                         | Stable identifier                         |
| `score`                      | Top-line score (depending on aggregation) |
| `pass_rate`                  | Pass rate over rows                       |
| `judge_results[judge_id]`    | Per-judge aggregated verdict              |
| `scorer_results[scorer_id]`  | Per-scorer aggregated verdict             |
| `rows`                       | Per-row details                           |
| `latency_ms_p50/p95/p99`     | Latency distribution                      |
| `cost_total`                 | ECU consumed                              |
| `created_at`, `completed_at` | Timestamps                                |

## Artifacts

Each evaluation produces:

* The result object above
* A row-level results dataset (browsable, exportable)
* Optional: a comparison artifact if part of a compare-models run
* Optional: a regression artifact if there's a baseline

## See also

* [Evaluations](/8.-evaluate-score-the-outputs/evaluations-1.md)
* [Stratix Premium — Evaluations](/8.-evaluate-score-the-outputs/evaluations.md)
* [SDK: evaluations](/8.-evaluate-score-the-outputs/evaluations-1.md)


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