Reasoning-Uad-Conflicting-Telemetry

The model receives the prompt (and optional system message). The run uses scorer rubric_json_metrics with the JSON configuration below. Pass/fail and partial credit are determined entirely by that scorer against the model output; no human grading.

Return JSON only with keys answer, evidence, constraints. Metrics show p95 latency doubled, traces show normal spans for sampled requests, and sampling was reduced from 10% to 1%. Explain why the evidence conflicts.

{
  "metrics": {
    "accuracy": {
      "checks": [
        {
          "contains": [
            "sampling"
          ]
        },
        {
          "contains": [
            "p95 latency"
          ]
        },
        {
          "contains": [
            "traces"
          ]
        }
      ]
    },
    "evidence": {
      "checks": [
        {
          "contains": [
            "reduced from 10% to 1%"
          ]
        },
        {
          "contains": [
            "normal spans"
          ]
        },
        {
          "contains": [
            "metrics"
          ]
        }
      ]
    },
    "constraint": {
      "checks": [
        {
          "contains": [
            "sample bias"
          ]
        },
        {
          "contains": [
            "cannot dismiss"
          ]
        },
        {
          "contains": [
            "uncertainty"
          ]
        }
      ]
    }
  }
}