{
  "model": "gemma4:26b",
  "edit_tool": "apply_patch",
  "tool_result_cap": 800,
  "workdir": "/home/claude/bin/gemma4-research/scripts/bakeoff/runs_patch/gemma4-26b-truncated/work",
  "started_at": 1776533701.8915875,
  "turns": [
    {
      "iteration": 1,
      "elapsed_s": 0.55,
      "content": "",
      "tool_calls": [
        {
          "name": "run_bash",
          "arguments": {
            "command": "ls -R"
          },
          "result": "exit=0\n--- stdout ---\n.:\ncalc\nREADME.md\ntests\n\n./calc:\n__init__.py\n__pycache__\nstats.py\n\n./calc/__pycache__:\n__init__.cpython-313.pyc\nstats.cpython-313.pyc\n\n./tests:\n__pycache__\ntest_stats.py\n\n./tests/__pycache__:\ntest_stats.cpython-313-pytest-9.0.2.pyc\n\n--- stderr ---\n"
        }
      ],
      "prompt_eval_count": 458,
      "eval_count": 21
    },
    {
      "iteration": 2,
      "elapsed_s": 0.61,
      "content": "",
      "tool_calls": [
        {
          "name": "read_file",
          "arguments": {
            "path": "README.md"
          },
          "result": "# Bakeoff Task\n\nA tiny Python package (`calc/`) with a statistics module. Run `pytest` from this\ndirectory \u2014 two tests currently fail because `median` returns the upper-middle\nelement instead of averaging the two middle elements on even-length inputs.\n\nYour job: make all tests pass. Do not disable or modify the tests.\n\nAllowed tools:\n- `read_file(path)` \u2014 read a file (relative to this directory)\n- `write_file(path, content)` \u2014 overwrite a file (relative to this directory)\n- `run_bash(command)` \u2014 run a shell command (cwd is this directory)\n\nWhen all tests pass, reply with a short summary of the fix and stop calling tools.\n"
        }
      ],
      "prompt_eval_count": 599,
      "eval_count": 21
    },
    {
      "iteration": 3,
      "elapsed_s": 0.64,
      "content": "",
      "tool_calls": [
        {
          "name": "run_bash",
          "arguments": {
            "command": "pytest"
          },
          "result": "exit=2\n--- stdout ---\n============================= test session starts ==============================\nplatform linux -- Python 3.13.5, pytest-9.0.2, pluggy-1.6.0\nrootdir: /home/claude/bin/gemma4-research/scripts/bakeoff/runs_patch/gemma4-26b-truncated/work\nplugins: asyncio-1.3.0, anyio-4.12.1\nasyncio: mode=Mode.STRICT, debug=False, asyncio_default_fixture_loop_scope=None, asyncio_default_test_loop_scope=function\ncollected 0 items / 1 error\n\n==================================== ERRORS ====================================\n_____________________ ERROR collecting tests/test_stats.py _____________________\nImportError while importing test module '/home/claude/bin/gemma4-research/scripts/bakeoff/runs_patch/gemma4-26b-truncated/work/tests/test_stats.py'.\nHint: make sure your test modules/packages "
        }
      ],
      "prompt_eval_count": 780,
      "eval_count": 19
    },
    {
      "iteration": 4,
      "elapsed_s": 0.76,
      "content": "",
      "tool_calls": [
        {
          "name": "read_file",
          "arguments": {
            "path": "tests/test_stats.py"
          },
          "result": "from calc.stats import mean, median, mode, variance\n\n\ndef test_mean_basic():\n    assert mean([1, 2, 3, 4, 5]) == 3.0\n\n\ndef test_median_odd():\n    assert median([1, 2, 3]) == 2\n\n\ndef test_median_even():\n    assert median([1, 2, 3, 4]) == 2.5\n\n\ndef test_median_unsorted():\n    assert median([3, 1, 4, 1, 5, 9, 2, 6]) == 3.5\n\n\ndef test_median_floats():\n    assert median([1.0, 2.0, 3.0, 4.0]) == 2.5\n\n\ndef test_mode_basic():\n    assert mode([1, 2, 2, 3]) == 2\n\n\ndef test_variance_basic():\n    # sample variance (n-1) of [1, 2, 3, 4, 5] is 10/4 = 2.5\n    assert variance([1, 2, 3, 4, 5]) == 2.5\n"
        }
      ],
      "prompt_eval_count": 1040,
      "eval_count": 25
    },
    {
      "iteration": 5,
      "elapsed_s": 0.83,
      "content": "",
      "tool_calls": [
        {
          "name": "run_bash",
          "arguments": {
            "command": "export PYTHONPATH=$PYTHONPATH:. && pytest"
          },
          "result": "exit=1\n--- stdout ---\n============================= test session starts ==============================\nplatform linux -- Python 3.13.5, pytest-9.0.2, pluggy-1.6.0\nrootdir: /home/claude/bin/gemma4-research/scripts/bakeoff/runs_patch/gemma4-26b-truncated/work\nplugins: asyncio-1.3.0, anyio-4.12.1\nasyncio: mode=Mode.STRICT, debug=False, asyncio_default_fixture_loop_scope=None, asyncio_default_test_loop_scope=function\ncollected 7 items\n\ntests/test_stats.py ..FFF..                                              [100%]\n\n=================================== FAILURES ===================================\n_______________________________ test_median_even _______________________________\n\n    def test_median_even():\n>       assert median([1, 2, 3, 4]) == 2.5\nE       assert 3 == 2.5\nE        +  where 3 = med"
        }
      ],
      "prompt_eval_count": 1343,
      "eval_count": 26
    },
    {
      "iteration": 6,
      "elapsed_s": 0.74,
      "content": "",
      "tool_calls": [
        {
          "name": "read_file",
          "arguments": {
            "path": "calc/stats.py"
          },
          "result": "\"\"\"Basic statistics helpers.\"\"\"\n\n\ndef mean(numbers):\n    \"\"\"Arithmetic mean of a non-empty list.\"\"\"\n    return sum(numbers) / len(numbers)\n\n\ndef median(numbers):\n    \"\"\"Return the median of a list of numbers.\"\"\"\n    s = sorted(numbers)\n    n = len(s)\n    return s[n // 2]\n\n\ndef mode(numbers):\n    \"\"\"Return the most common value. Ties broken by first occurrence.\"\"\"\n    counts = {}\n    for x in numbers:\n        counts[x] = counts.get(x, 0) + 1\n    best = None\n    best_count = -1\n    for x in numbers:\n        if counts[x] > best_count:\n            best = x\n            best_count = counts[x]\n    return best\n\n\ndef variance(numbers):\n    \"\"\"Sample variance (divides by n-1).\"\"\"\n    if len(numbers) < 2:\n        raise ValueError(\"variance requires at least 2 values\")\n    m = mean(numbers)\n    return"
        }
      ],
      "prompt_eval_count": 1611,
      "eval_count": 23
    },
    {
      "iteration": 7,
      "elapsed_s": 0.76,
      "content": "",
      "tool_calls": [
        {
          "name": "read_file",
          "arguments": {
            "path": "calc/stats.py"
          },
          "result": "\"\"\"Basic statistics helpers.\"\"\"\n\n\ndef mean(numbers):\n    \"\"\"Arithmetic mean of a non-empty list.\"\"\"\n    return sum(numbers) / len(numbers)\n\n\ndef median(numbers):\n    \"\"\"Return the median of a list of numbers.\"\"\"\n    s = sorted(numbers)\n    n = len(s)\n    return s[n // 2]\n\n\ndef mode(numbers):\n    \"\"\"Return the most common value. Ties broken by first occurrence.\"\"\"\n    counts = {}\n    for x in numbers:\n        counts[x] = counts.get(x, 0) + 1\n    best = None\n    best_count = -1\n    for x in numbers:\n        if counts[x] > best_count:\n            best = x\n            best_count = counts[x]\n    return best\n\n\ndef variance(numbers):\n    \"\"\"Sample variance (divides by n-1).\"\"\"\n    if len(numbers) < 2:\n        raise ValueError(\"variance requires at least 2 values\")\n    m = mean(numbers)\n    return"
        }
      ],
      "prompt_eval_count": 1876,
      "eval_count": 23
    },
    {
      "iteration": 8,
      "elapsed_s": 0.76,
      "content": "",
      "tool_calls": [
        {
          "name": "run_bash",
          "arguments": {
            "command": "cat calc/stats.py"
          },
          "result": "exit=0\n--- stdout ---\n\"\"\"Basic statistics helpers.\"\"\"\n\n\ndef mean(numbers):\n    \"\"\"Arithmetic mean of a non-empty list.\"\"\"\n    return sum(numbers) / len(numbers)\n\n\ndef median(numbers):\n    \"\"\"Return the median of a list of numbers.\"\"\"\n    s = sorted(numbers)\n    n = len(s)\n    return s[n // 2]\n\n\ndef mode(numbers):\n    \"\"\"Return the most common value. Ties broken by first occurrence.\"\"\"\n    counts = {}\n    for x in numbers:\n        counts[x] = counts.get(x, 0) + 1\n    best = None\n    best_count = -1\n    for x in numbers:\n        if counts[x] > best_count:\n            best = x\n            best_count = counts[x]\n    return best\n\n\ndef variance(numbers):\n    \"\"\"Sample variance (divides by n-1).\"\"\"\n    if len(numbers) < 2:\n        raise ValueError(\"variance requires at least 2 values\")\n    m = me"
        }
      ],
      "prompt_eval_count": 2141,
      "eval_count": 24
    },
    {
      "iteration": 9,
      "elapsed_s": 0.78,
      "content": "",
      "tool_calls": [
        {
          "name": "run_bash",
          "arguments": {
            "command": "cat calc/stats.py"
          },
          "result": "exit=0\n--- stdout ---\n\"\"\"Basic statistics helpers.\"\"\"\n\n\ndef mean(numbers):\n    \"\"\"Arithmetic mean of a non-empty list.\"\"\"\n    return sum(numbers) / len(numbers)\n\n\ndef median(numbers):\n    \"\"\"Return the median of a list of numbers.\"\"\"\n    s = sorted(numbers)\n    n = len(s)\n    return s[n // 2]\n\n\ndef mode(numbers):\n    \"\"\"Return the most common value. Ties broken by first occurrence.\"\"\"\n    counts = {}\n    for x in numbers:\n        counts[x] = counts.get(x, 0) + 1\n    best = None\n    best_count = -1\n    for x in numbers:\n        if counts[x] > best_count:\n            best = x\n            best_count = counts[x]\n    return best\n\n\ndef variance(numbers):\n    \"\"\"Sample variance (divides by n-1).\"\"\"\n    if len(numbers) < 2:\n        raise ValueError(\"variance requires at least 2 values\")\n    m = me"
        }
      ],
      "prompt_eval_count": 2409,
      "eval_count": 24
    },
    {
      "iteration": 10,
      "elapsed_s": 0.79,
      "content": "",
      "tool_calls": [
        {
          "name": "run_bash",
          "arguments": {
            "command": "cat calc/stats.py"
          },
          "result": "exit=0\n--- stdout ---\n\"\"\"Basic statistics helpers.\"\"\"\n\n\ndef mean(numbers):\n    \"\"\"Arithmetic mean of a non-empty list.\"\"\"\n    return sum(numbers) / len(numbers)\n\n\ndef median(numbers):\n    \"\"\"Return the median of a list of numbers.\"\"\"\n    s = sorted(numbers)\n    n = len(s)\n    return s[n // 2]\n\n\ndef mode(numbers):\n    \"\"\"Return the most common value. Ties broken by first occurrence.\"\"\"\n    counts = {}\n    for x in numbers:\n        counts[x] = counts.get(x, 0) + 1\n    best = None\n    best_count = -1\n    for x in numbers:\n        if counts[x] > best_count:\n            best = x\n            best_count = counts[x]\n    return best\n\n\ndef variance(numbers):\n    \"\"\"Sample variance (divides by n-1).\"\"\"\n    if len(numbers) < 2:\n        raise ValueError(\"variance requires at least 2 values\")\n    m = me"
        }
      ],
      "prompt_eval_count": 2677,
      "eval_count": 24
    },
    {
      "iteration": 11,
      "elapsed_s": 0.78,
      "content": "",
      "tool_calls": [
        {
          "name": "run_bash",
          "arguments": {
            "command": "cat calc/stats.py"
          },
          "result": "exit=0\n--- stdout ---\n\"\"\"Basic statistics helpers.\"\"\"\n\n\ndef mean(numbers):\n    \"\"\"Arithmetic mean of a non-empty list.\"\"\"\n    return sum(numbers) / len(numbers)\n\n\ndef median(numbers):\n    \"\"\"Return the median of a list of numbers.\"\"\"\n    s = sorted(numbers)\n    n = len(s)\n    return s[n // 2]\n\n\ndef mode(numbers):\n    \"\"\"Return the most common value. Ties broken by first occurrence.\"\"\"\n    counts = {}\n    for x in numbers:\n        counts[x] = counts.get(x, 0) + 1\n    best = None\n    best_count = -1\n    for x in numbers:\n        if counts[x] > best_count:\n            best = x\n            best_count = counts[x]\n    return best\n\n\ndef variance(numbers):\n    \"\"\"Sample variance (divides by n-1).\"\"\"\n    if len(numbers) < 2:\n        raise ValueError(\"variance requires at least 2 values\")\n    m = me"
        }
      ],
      "prompt_eval_count": 2945,
      "eval_count": 24
    },
    {
      "iteration": 12,
      "elapsed_s": 0.8,
      "content": "",
      "tool_calls": [
        {
          "name": "run_bash",
          "arguments": {
            "command": "ls -l calc/stats.py"
          },
          "result": "exit=0\n--- stdout ---\n-rw-rw-r-- 1 claude claude 857 Apr 18 13:19 calc/stats.py\n\n--- stderr ---\n"
        }
      ],
      "prompt_eval_count": 3213,
      "eval_count": 26
    },
    {
      "iteration": 13,
      "elapsed_s": 0.63,
      "content": "",
      "tool_calls": [
        {
          "name": "read_file",
          "arguments": {
            "path": "calc/stats.py"
          },
          "result": "\"\"\"Basic statistics helpers.\"\"\"\n\n\ndef mean(numbers):\n    \"\"\"Arithmetic mean of a non-empty list.\"\"\"\n    return sum(numbers) / len(numbers)\n\n\ndef median(numbers):\n    \"\"\"Return the median of a list of numbers.\"\"\"\n    s = sorted(numbers)\n    n = len(s)\n    return s[n // 2]\n\n\ndef mode(numbers):\n    \"\"\"Return the most common value. Ties broken by first occurrence.\"\"\"\n    counts = {}\n    for x in numbers:\n        counts[x] = counts.get(x, 0) + 1\n    best = None\n    best_count = -1\n    for x in numbers:\n        if counts[x] > best_count:\n            best = x\n            best_count = counts[x]\n    return best\n\n\ndef variance(numbers):\n    \"\"\"Sample variance (divides by n-1).\"\"\"\n    if len(numbers) < 2:\n        raise ValueError(\"variance requires at least 2 values\")\n    m = mean(numbers)\n    return"
        }
      ],
      "prompt_eval_count": 3288,
      "eval_count": 23
    },
    {
      "iteration": 14,
      "elapsed_s": 2.44,
      "content": "",
      "tool_calls": [
        {
          "name": "apply_patch",
          "arguments": {
            "new_text": "def median(numbers):\n    \"\"\"Return the median of a list of numbers.\"\"\"\n    s = sorted(numbers)\n    n = len(s)\n    if n % 2 == 1:\n        return s[n // 2]\n    else:\n        return (s[n // 2 - 1] + s[n // 2]) / 2",
            "old_text": "def median(numbers):\n    \"\"\"Return the median of a list of numbers.\"\"\"\n    s = sorted(numbers)\n    n = len(s)\n    return s[n // 2]",
            "path": "calc/stats.py"
          },
          "result": "patched calc/stats.py (replaced 130 chars with 210 chars)"
        }
      ],
      "prompt_eval_count": 3553,
      "eval_count": 163
    },
    {
      "iteration": 15,
      "elapsed_s": 0.74,
      "content": "",
      "tool_calls": [
        {
          "name": "run_bash",
          "arguments": {
            "command": "cat calc/stats.py"
          },
          "result": "exit=0\n--- stdout ---\n\"\"\"Basic statistics helpers.\"\"\"\n\n\ndef mean(numbers):\n    \"\"\"Arithmetic mean of a non-empty list.\"\"\"\n    return sum(numbers) / len(numbers)\n\n\ndef median(numbers):\n    \"\"\"Return the median of a list of numbers.\"\"\"\n    s = sorted(numbers)\n    n = len(s)\n    if n % 2 == 1:\n        return s[n // 2]\n    else:\n        return (s[n // 2 - 1] + s[n // 2]) / 2\n\n\ndef mode(numbers):\n    \"\"\"Return the most common value. Ties broken by first occurrence.\"\"\"\n    counts = {}\n    for x in numbers:\n        counts[x] = counts.get(x, 0) + 1\n    best = None\n    best_count = -1\n    for x in numbers:\n        if counts[x] > best_count:\n            best = x\n            best_count = counts[x]\n    return best\n\n\ndef variance(numbers):\n    \"\"\"Sample variance (divides by n-1).\"\"\"\n    if len(numbers)"
        }
      ],
      "prompt_eval_count": 3741,
      "eval_count": 24
    }
  ],
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    "tests_pass": true,
    "iterations_used": 15,
    "tool_call_counts": {
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      "apply_patch": 1,
      "run_bash": 9
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    "wall_clock_s": 13.35
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}