{
  "created_utc": "2026-10-21T14:52:02.386148+00:00",
  "model": {
    "model_id": "Qwen/Qwen2.5-1.5B-Instruct",
    "revision": "989aa7980e4cf806f80c7fef2b1adb7bc71aa306"
  },
  "runtime": {
    "python": "3.12.14",
    "torch": "2.14.1",
    "transformers": "4.57.1",
    "platform": "macOS-27.0.1-arm64-arm-64bit",
    "device": "cpu",
    "dtype": "float32",
    "threads": 2
  },
  "calls": [
    {
      "messages": [
        {
          "role": "system",
          "content": "Extract sampling distribution and sample size. The interval formula does not determine the sampling distribution. Only normal and exponential are supported. Return exactly family and n, following these JSON examples."
        },
        {
          "role": "user",
          "content": "Use exponential observations with sample size 10."
        },
        {
          "role": "assistant",
          "content": "{\"family\":\"exponential\",\"n\":10}"
        },
        {
          "role": "user",
          "content": "Use uniform observations with sample size 15."
        },
        {
          "role": "assistant",
          "content": "{\"family\":\"unsupported\",\"n\":15}"
        },
        {
          "role": "user",
          "content": "Use iid normal observations with sample size 18 to estimate coverage of the mean plus or minus 1.96 estimated standard errors."
        }
      ],
      "raw": "{\"family\":\"normal\",\"n\":18}",
      "prompt_tokens": 137,
      "generated_tokens": 11,
      "max_new_tokens": 128,
      "stop_reason": "eos",
      "elapsed_seconds": 2.139
    },
    {
      "messages": [
        {
          "role": "system",
          "content": "Extract sampling distribution and sample size. The interval formula does not determine the sampling distribution. Only normal and exponential are supported. Return exactly family and n, following these JSON examples."
        },
        {
          "role": "user",
          "content": "Use exponential observations with sample size 10."
        },
        {
          "role": "assistant",
          "content": "{\"family\":\"exponential\",\"n\":10}"
        },
        {
          "role": "user",
          "content": "Use uniform observations with sample size 15."
        },
        {
          "role": "assistant",
          "content": "{\"family\":\"unsupported\",\"n\":15}"
        },
        {
          "role": "user",
          "content": "Use iid exponential observations with sample size 45 to estimate coverage of the mean plus or minus 1.96 estimated standard errors."
        }
      ],
      "raw": "{\"family\":\"exponential\",\"n\":45}",
      "prompt_tokens": 137,
      "generated_tokens": 12,
      "max_new_tokens": 128,
      "stop_reason": "eos",
      "elapsed_seconds": 1.343
    },
    {
      "messages": [
        {
          "role": "system",
          "content": "Extract sampling distribution and sample size. The interval formula does not determine the sampling distribution. Only normal and exponential are supported. Return exactly family and n, following these JSON examples."
        },
        {
          "role": "user",
          "content": "Use exponential observations with sample size 10."
        },
        {
          "role": "assistant",
          "content": "{\"family\":\"exponential\",\"n\":10}"
        },
        {
          "role": "user",
          "content": "Use uniform observations with sample size 15."
        },
        {
          "role": "assistant",
          "content": "{\"family\":\"unsupported\",\"n\":15}"
        },
        {
          "role": "user",
          "content": "Use iid Cauchy observations with sample size 22 to estimate coverage."
        }
      ],
      "raw": "{\"family\":\"cauchy\",\"n\":22}",
      "prompt_tokens": 125,
      "generated_tokens": 13,
      "max_new_tokens": 128,
      "stop_reason": "eos",
      "elapsed_seconds": 1.351
    }
  ],
  "results": [
    {
      "question": "Use iid normal observations with sample size 18 to estimate coverage of the mean plus or minus 1.96 estimated standard errors.",
      "report_kind": "deterministic_template",
      "request": {
        "family": "normal",
        "n": 18
      },
      "status": "completed",
      "tool_result": {
        "family": "normal",
        "n": 18,
        "estimate": 0.926,
        "repetitions": 500,
        "mc_interval": [
          0.8996646988891734,
          0.945839126122497
        ],
        "seed": 2026
      },
      "report": "For iid normal samples with n=18, the approximate z interval's estimated coverage is 0.926 from 500 repetitions. The approximate 95% Monte Carlo interval for that coverage probability is [0.900, 0.946]. The interval procedure's nominal 95% label does not guarantee its actual coverage.",
      "intent_correct": true,
      "task_success": true
    },
    {
      "question": "Use iid exponential observations with sample size 45 to estimate coverage of the mean plus or minus 1.96 estimated standard errors.",
      "report_kind": "deterministic_template",
      "request": {
        "family": "exponential",
        "n": 45
      },
      "status": "completed",
      "tool_result": {
        "family": "exponential",
        "n": 45,
        "estimate": 0.938,
        "repetitions": 500,
        "mc_interval": [
          0.9133397667805389,
          0.9559810673863897
        ],
        "seed": 2026
      },
      "report": "For iid exponential samples with n=45, the approximate z interval's estimated coverage is 0.938 from 500 repetitions. The approximate 95% Monte Carlo interval for that coverage probability is [0.913, 0.956]. The interval procedure's nominal 95% label does not guarantee its actual coverage.",
      "intent_correct": true,
      "task_success": true
    },
    {
      "question": "Use iid Cauchy observations with sample size 22 to estimate coverage.",
      "report_kind": "deterministic_template",
      "status": "invalid",
      "error": "Unrecognized family",
      "intent_correct": false,
      "task_success": false
    }
  ],
  "protocol": "Guided development demonstration. Actual local model calls; no hidden answer replacement. Authored tasks, not a sampled population benchmark.",
  "source_sha256": {
    "contracts.py": "acc74ce5b77896098ff3c6e0d4f1018b0430d65b70fd7e1053db4bea95156fa2",
    "llm_lab.py": "365e679ce038c2a2386d40540d44d7af13d139850f0464e1f621a29143c28436",
    "rag_core.py": "c989148b7710f1e4d700cdd7574ab97a247fa3fd7932236319441ca50d91bac2",
    "guided_systems.py": "7e96d0b75a98efb6651a0167f72ddcf9e70b75f49e086283b39087da2c27e1d7",
    "notebook_support.py": "28827967eff892b837d4068ed1883ea78a4dbb20d712a79f8afc048193554594"
  }
}