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+ {"schema": 2, "epoch": 88162, "nonce": "8ec68d7a540eaca2", "hotkey": "5CDRYdHggymECVATzv8rRM2PK7H2kq1vnC6rgajpKmNTzoTs", "source_hash": "99c181689478bebe33c6b8f8fd28184cc79a2cc3d5cc1ef3e2c799f442f28e0d", "weights_hash": "928ebf362cb5ad6d2b22321c1cb8ca540d676bacc1fcf6a150f6f3d86132e185", "model_id": "injected", "total_cost_usd": 0.0021875, "n_calls": 6, "call_log_hash": "fa038a3b40da42866e06f45450aa8a8e8c0d9060a52762bbec30bbfbcae895c2", "measurement": "1449fadb4821cadef93f7eecc8c3b040e2cd244e01a2607ea531e5f7055c38d8", "confined": true, "latency_s": 47.608, "tokens_in": 1908, "tokens_out": 3276, "results": [{"benchmark": "mmlu", "task_id": "mmlu-10344", "answer": "B", "cost_usd": 1.37e-05, "chosen_rung": -1, "rungs_used": [], "distribution": []}, {"benchmark": "mmlu", "task_id": "mmlu-7560", "answer": "B", "cost_usd": 7.500000000000001e-06, "chosen_rung": -1, "rungs_used": [], "distribution": []}, {"benchmark": "math", "task_id": "gsm8k-1101", "answer": "Amber ran 8 miles.\n\nMicah ran \\(3.5 \\times 8 = 28\\) miles.\n\nTogether, Amber and Micah ran \\(8 + 28 = 36\\) miles.\n\nAhito ran \\(52 - 36 = 16\\) miles.\n\n16", "cost_usd": 7.94e-05, "chosen_rung": -1, "rungs_used": [], "distribution": []}, {"benchmark": "math", "task_id": "gsm8k-276", "answer": "There were \\(80\\) cards total.\n\n- Cards with A: \\(\\frac{2}{5}\\times 80=32\\)\n- Remaining: \\(80-32=48\\)\n- Cards with B: \\(\\frac{1}{2}\\times 48=24\\)\n- Remaining: \\(48-24=24\\)\n- Cards with C: \\(\\frac{5}{8}\\times 24=15\\)\n- Cards with D: \\(24-15=9\\)\n\n9", "cost_usd": 0.0001114, "chosen_rung": -1, "rungs_used": [], "distribution": []}, {"benchmark": "code", "task_id": "lcb-abc391_a", "answer": "import sys\n\nopposite = {\n \"N\": \"S\",\n \"S\": \"N\",\n \"E\": \"W\",\n \"W\": \"E\",\n \"NE\": \"SW\",\n \"SW\": \"NE\",\n \"NW\": \"SE\",\n \"SE\": \"NW\",\n}\n\nd = sys.stdin.buffer.readline().strip().decode()\nsys.stdout.write(opposite[d] + \"\\n\")\n", "cost_usd": 8.150000000000003e-05, "chosen_rung": -1, "rungs_used": [], "distribution": []}, {"benchmark": "code", "task_id": "lcb-abc400_d", "answer": "import sys\nfrom collections import deque\nfrom array import array\n\ndef main():\n input = sys.stdin.buffer.readline\n H, W = map(int, input().split())\n grid = b\"\".join(input().strip() for _ in range(H))\n A, B, C, D = map(int, input().split())\n start = (A - 1) * W + (B - 1)\n target = (C - 1) * W + (D - 1)\n\n n = H * W\n inf = 10**9\n dist = array(\"i\", [inf]) * n\n used = bytearray(n)\n dist[start] = 0\n\n q = deque([start])\n while q:\n v = q.popleft()\n if used[v]:\n continue\n used[v] = 1\n\n if v == target:\n break\n\n r, c = divmod(v, W)\n nd = dist[v]\n\n if r > 0:\n u = v - W\n if grid[u] == 46 and not used[u] and nd < dist[u]:\n dist[u] = nd\n q.appendleft(u)\n if r + 1 < H:\n u = v + W\n if grid[u] == 46 and not used[u] and nd < dist[u]:\n dist[u] = nd\n q.appendleft(u)\n if c > 0:\n u = v - 1\n if grid[u] == 46 and not used[u] and nd < dist[u]:\n dist[u] = nd\n q.appendleft(u)\n if c + 1 < W:\n u = v + 1\n if grid[u] == 46 and not used[u] and nd < dist[u]:\n dist[u] = nd\n q.appendleft(u)\n\n nd += 1\n\n if r > 0:\n u = v - W\n if not used[u] and nd < dist[u]:\n dist[u] = nd\n q.append(u)\n if r > 1:\n u = v - 2 * W\n if not used[u] and nd < dist[u]:\n dist[u] = nd\n q.append(u)\n\n if r + 1 < H:\n u = v + W\n if not used[u] and nd < dist[u]:\n dist[u] = nd\n q.append(u)\n if r + 2 < H:\n u = v + 2 * W\n if not used[u] and nd < dist[u]:\n dist[u] = nd\n q.append(u)\n\n if c > 0:\n u = v - 1\n if not used[u] and nd < dist[u]:\n dist[u] = nd\n q.append(u)\n if c > 1:\n u = v - 2\n if not used[u] and nd < dist[u]:\n dist[u] = nd\n q.append(u)\n\n if c + 1 < W:\n u = v + 1\n if not used[u] and nd < dist[u]:\n dist[u] = nd\n q.append(u)\n if c + 2 < W:\n u = v + 2\n if not used[u] and nd < dist[u]:\n dist[u] = nd\n q.append(u)\n\n print(dist[target])\n\nif __name__ == \"__main__\":\n main()\n", "cost_usd": 0.0018940000000000003, "chosen_rung": -1, "rungs_used": [], "distribution": []}], "quote": {"measurement": "1449fadb4821cadef93f7eecc8c3b040e2cd244e01a2607ea531e5f7055c38d8", "report_data": "37e41bbb4c9cf1484fabfea7c22ab52a7f1100f58a8787d99b7e8068f271360e", "platform_sig": 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