{"abstract":"A dead horizontal channel drags ML down by 1.5 units.","category":"Seismic magnitude estimation","checks":8,"contract":"Zero-to-peak Wood-Anderson amplitudes on two horizontal components in mm (0 = dead channel, ignored; both dead returns None). -log A0 is linearly interpolated from [(0,1.4),(10,1.5),(20,1.7),(30,2.1),(50,2.6),(100,3.0),(200,3.5),(300,4.0),(400,4.5),(600,5.1)] with 0 <= dist <= 600 inclusive, else None. ML = mean of per-component log10 amplitudes + (-log A0), rounded 0.01.","evaluation_group":"w2-seismic_magnitude_estimation-richter-a0-table","failed_approach":"A 0.1 mm floor discards genuine small amplitudes.","family":"w2-seismic_magnitude_estimation-richter-a0-table-dead-channel-exclusion","id":"FA-71706","implementations":{"attempt":{"sha256":"fbe0baa408ec79372de411b65c2fe9d21d8b6fbf8b47a87c4f5c7210e8c39167","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport math\nN = 1\nobservations = []\ndef solve(amp_n_mm, amp_e_mm, dist_km):\n    table = [(0, 1.4), (10, 1.5), (20, 1.7), (30, 2.1), (50, 2.6), (100, 3.0), (200, 3.5), (300, 4.0), (400, 4.5), (600, 5.1)]\n    if dist_km < 0 or dist_km > 600:\n        return None\n    comps = [a for a in (amp_n_mm, amp_e_mm) if a > 0.1]\n    if not comps:\n        return None\n    corr = None\n    for (d0, c0), (d1, c1) in zip(table, table[1:]):\n        if d0 <= dist_km <= d1:\n            corr = c0 + (c1 - c0) * (dist_km - d0) / (d1 - d0)\n            break\n    logs = [math.log10(a) for a in comps]\n    return round(sum(logs) / len(logs) + corr, 2)\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['N 1.0 mm E 1.0 mm at 0 km', [1.0, 1.0, 0], 1.4], ['N 1.0 mm E 1.0 mm at 5 km', [1.0, 1.0, 5], 1.45], ['N 1.0 mm E 1.0 mm at 10 km', [1.0, 1.0, 10], 1.5], ['N 1.0 mm E 1.0 mm at 25 km', [1.0, 1.0, 25], 1.9], ['N 1.0 mm E 1.0 mm at 50 km', [1.0, 1.0, 50], 2.6], ['N 1.0 mm E 1.0 mm at 75 km', [1.0, 1.0, 75], 2.8], ['N 12.0 mm E 0.0 mm at 0 km', [12.0, 0.0, 0], 2.48], ['N 0.05 mm E 0.08 mm at 5 km', [0.05, 0.08, 5], 0.25]], [['N 1.0 mm E 1.0 mm at 600 km', [1.0, 1.0, 600], 5.1], ['N 1.0 mm E 1.0 mm at 650 km', [1.0, 1.0, 650], None], ['N 0.2 mm E 5.0 mm at 0 km', [0.2, 5.0, 0], 1.4], ['N 0.2 mm E 5.0 mm at 5 km', [0.2, 5.0, 5], 1.45], ['N 0.2 mm E 5.0 mm at 10 km', [0.2, 5.0, 10], 1.5], ['N 0.2 mm E 5.0 mm at 25 km', [0.2, 5.0, 25], 1.9], ['N 12.0 mm E 0.0 mm at 25 km', [12.0, 0.0, 25], 2.98], ['N 0.05 mm E 0.08 mm at 150 km', [0.05, 0.08, 150], 2.05]], [['N 0.2 mm E 5.0 mm at 75 km', [0.2, 5.0, 75], 2.8], ['N 0.2 mm E 5.0 mm at 150 km', [0.2, 5.0, 150], 3.25], ['N 0.2 mm E 5.0 mm at 600 km', [0.2, 5.0, 600], 5.1], ['N 0.2 mm E 5.0 mm at 650 km', [0.2, 5.0, 650], None], ['N 12.0 mm E 0.0 mm at 0 km', [12.0, 0.0, 0], 2.48], ['N 12.0 mm E 0.0 mm at 5 km', [12.0, 0.0, 5], 2.53], ['N 12.0 mm E 0.0 mm at 150 km', [12.0, 0.0, 150], 4.33], ['N 0.05 mm E 0.08 mm at 25 km', [0.05, 0.08, 25], 0.7]], [['N 12.0 mm E 0.0 mm at 25 km', [12.0, 0.0, 25], 2.98], ['N 12.0 mm E 0.0 mm at 50 km', [12.0, 0.0, 50], 3.68], ['N 12.0 mm E 0.0 mm at 75 km', [12.0, 0.0, 75], 3.88], ['N 12.0 mm E 0.0 mm at 150 km', [12.0, 0.0, 150], 4.33], ['N 12.0 mm E 0.0 mm at 600 km', [12.0, 0.0, 600], 6.18], ['N 12.0 mm E 0.0 mm at 650 km', [12.0, 0.0, 650], None], ['N 0.0 mm E 0.0 mm at 5 km', [0.0, 0.0, 5], None], ['N 0.05 mm E 0.08 mm at 0 km', [0.05, 0.08, 0], 0.2]], [['N 0.0 mm E 0.0 mm at 5 km', [0.0, 0.0, 5], None], ['N 0.0 mm E 0.0 mm at 10 km', [0.0, 0.0, 10], None], ['N 0.0 mm E 0.0 mm at 25 km', [0.0, 0.0, 25], None], ['N 0.0 mm E 0.0 mm at 50 km', [0.0, 0.0, 50], None], ['N 0.0 mm E 0.0 mm at 75 km', [0.0, 0.0, 75], None], ['N 0.0 mm E 0.0 mm at 150 km', [0.0, 0.0, 150], None], ['N 0.0 mm E 0.0 mm at 600 km', [0.0, 0.0, 600], None], ['N 0.05 mm E 0.08 mm at 75 km', [0.05, 0.08, 75], 1.6]]]\nfor label, args, expected in fixtures[N - 1]:\n    check(label, solve(*args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"},"broken":{"sha256":"c240e0b991688975a221927eba9e5f655cf23df901820dde80d8b2ccc6654bb9","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport math\nN = 1\nobservations = []\ndef solve(amp_n_mm, amp_e_mm, dist_km):\n    table = [(0, 1.4), (10, 1.5), (20, 1.7), (30, 2.1), (50, 2.6), (100, 3.0), (200, 3.5), (300, 4.0), (400, 4.5), (600, 5.1)]\n    if dist_km < 0 or dist_km > 600:\n        return None\n    comps = [max(a, 1e-3) for a in (amp_n_mm, amp_e_mm)]\n    if not comps:\n        return None\n    corr = None\n    for (d0, c0), (d1, c1) in zip(table, table[1:]):\n        if d0 <= dist_km <= d1:\n            corr = c0 + (c1 - c0) * (dist_km - d0) / (d1 - d0)\n            break\n    logs = [math.log10(a) for a in comps]\n    return round(sum(logs) / len(logs) + corr, 2)\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['N 1.0 mm E 1.0 mm at 0 km', [1.0, 1.0, 0], 1.4], ['N 1.0 mm E 1.0 mm at 5 km', [1.0, 1.0, 5], 1.45], ['N 1.0 mm E 1.0 mm at 10 km', [1.0, 1.0, 10], 1.5], ['N 1.0 mm E 1.0 mm at 25 km', [1.0, 1.0, 25], 1.9], ['N 1.0 mm E 1.0 mm at 50 km', [1.0, 1.0, 50], 2.6], ['N 1.0 mm E 1.0 mm at 75 km', [1.0, 1.0, 75], 2.8], ['N 12.0 mm E 0.0 mm at 0 km', [12.0, 0.0, 0], 2.48], ['N 0.05 mm E 0.08 mm at 5 km', [0.05, 0.08, 5], 0.25]], [['N 1.0 mm E 1.0 mm at 600 km', [1.0, 1.0, 600], 5.1], ['N 1.0 mm E 1.0 mm at 650 km', [1.0, 1.0, 650], None], ['N 0.2 mm E 5.0 mm at 0 km', [0.2, 5.0, 0], 1.4], ['N 0.2 mm E 5.0 mm at 5 km', [0.2, 5.0, 5], 1.45], ['N 0.2 mm E 5.0 mm at 10 km', [0.2, 5.0, 10], 1.5], ['N 0.2 mm E 5.0 mm at 25 km', [0.2, 5.0, 25], 1.9], ['N 12.0 mm E 0.0 mm at 25 km', [12.0, 0.0, 25], 2.98], ['N 0.05 mm E 0.08 mm at 150 km', [0.05, 0.08, 150], 2.05]], [['N 0.2 mm E 5.0 mm at 75 km', [0.2, 5.0, 75], 2.8], ['N 0.2 mm E 5.0 mm at 150 km', [0.2, 5.0, 150], 3.25], ['N 0.2 mm E 5.0 mm at 600 km', [0.2, 5.0, 600], 5.1], ['N 0.2 mm E 5.0 mm at 650 km', [0.2, 5.0, 650], None], ['N 12.0 mm E 0.0 mm at 0 km', [12.0, 0.0, 0], 2.48], ['N 12.0 mm E 0.0 mm at 5 km', [12.0, 0.0, 5], 2.53], ['N 12.0 mm E 0.0 mm at 150 km', [12.0, 0.0, 150], 4.33], ['N 0.05 mm E 0.08 mm at 25 km', [0.05, 0.08, 25], 0.7]], [['N 12.0 mm E 0.0 mm at 25 km', [12.0, 0.0, 25], 2.98], ['N 12.0 mm E 0.0 mm at 50 km', [12.0, 0.0, 50], 3.68], ['N 12.0 mm E 0.0 mm at 75 km', [12.0, 0.0, 75], 3.88], ['N 12.0 mm E 0.0 mm at 150 km', [12.0, 0.0, 150], 4.33], ['N 12.0 mm E 0.0 mm at 600 km', [12.0, 0.0, 600], 6.18], ['N 12.0 mm E 0.0 mm at 650 km', [12.0, 0.0, 650], None], ['N 0.0 mm E 0.0 mm at 5 km', [0.0, 0.0, 5], None], ['N 0.05 mm E 0.08 mm at 0 km', [0.05, 0.08, 0], 0.2]], [['N 0.0 mm E 0.0 mm at 5 km', [0.0, 0.0, 5], None], ['N 0.0 mm E 0.0 mm at 10 km', [0.0, 0.0, 10], None], ['N 0.0 mm E 0.0 mm at 25 km', [0.0, 0.0, 25], None], ['N 0.0 mm E 0.0 mm at 50 km', [0.0, 0.0, 50], None], ['N 0.0 mm E 0.0 mm at 75 km', [0.0, 0.0, 75], None], ['N 0.0 mm E 0.0 mm at 150 km', [0.0, 0.0, 150], None], ['N 0.0 mm E 0.0 mm at 600 km', [0.0, 0.0, 600], None], ['N 0.05 mm E 0.08 mm at 75 km', [0.05, 0.08, 75], 1.6]]]\nfor label, args, expected in fixtures[N - 1]:\n    check(label, solve(*args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"},"fixed":{"sha256":"d670ca1fb6068669400541dbfdc7bc61b0628031bd867d2bf11fbfaedc104625","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport math\nN = 1\nobservations = []\ndef solve(amp_n_mm, amp_e_mm, dist_km):\n    table = [(0, 1.4), (10, 1.5), (20, 1.7), (30, 2.1), (50, 2.6), (100, 3.0), (200, 3.5), (300, 4.0), (400, 4.5), (600, 5.1)]\n    if dist_km < 0 or dist_km > 600:\n        return None\n    comps = [a for a in (amp_n_mm, amp_e_mm) if a > 0]\n    if not comps:\n        return None\n    corr = None\n    for (d0, c0), (d1, c1) in zip(table, table[1:]):\n        if d0 <= dist_km <= d1:\n            corr = c0 + (c1 - c0) * (dist_km - d0) / (d1 - d0)\n            break\n    logs = [math.log10(a) for a in comps]\n    return round(sum(logs) / len(logs) + corr, 2)\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['N 1.0 mm E 1.0 mm at 0 km', [1.0, 1.0, 0], 1.4], ['N 1.0 mm E 1.0 mm at 5 km', [1.0, 1.0, 5], 1.45], ['N 1.0 mm E 1.0 mm at 10 km', [1.0, 1.0, 10], 1.5], ['N 1.0 mm E 1.0 mm at 25 km', [1.0, 1.0, 25], 1.9], ['N 1.0 mm E 1.0 mm at 50 km', [1.0, 1.0, 50], 2.6], ['N 1.0 mm E 1.0 mm at 75 km', [1.0, 1.0, 75], 2.8], ['N 12.0 mm E 0.0 mm at 0 km', [12.0, 0.0, 0], 2.48], ['N 0.05 mm E 0.08 mm at 5 km', [0.05, 0.08, 5], 0.25]], [['N 1.0 mm E 1.0 mm at 600 km', [1.0, 1.0, 600], 5.1], ['N 1.0 mm E 1.0 mm at 650 km', [1.0, 1.0, 650], None], ['N 0.2 mm E 5.0 mm at 0 km', [0.2, 5.0, 0], 1.4], ['N 0.2 mm E 5.0 mm at 5 km', [0.2, 5.0, 5], 1.45], ['N 0.2 mm E 5.0 mm at 10 km', [0.2, 5.0, 10], 1.5], ['N 0.2 mm E 5.0 mm at 25 km', [0.2, 5.0, 25], 1.9], ['N 12.0 mm E 0.0 mm at 25 km', [12.0, 0.0, 25], 2.98], ['N 0.05 mm E 0.08 mm at 150 km', [0.05, 0.08, 150], 2.05]], [['N 0.2 mm E 5.0 mm at 75 km', [0.2, 5.0, 75], 2.8], ['N 0.2 mm E 5.0 mm at 150 km', [0.2, 5.0, 150], 3.25], ['N 0.2 mm E 5.0 mm at 600 km', [0.2, 5.0, 600], 5.1], ['N 0.2 mm E 5.0 mm at 650 km', [0.2, 5.0, 650], None], ['N 12.0 mm E 0.0 mm at 0 km', [12.0, 0.0, 0], 2.48], ['N 12.0 mm E 0.0 mm at 5 km', [12.0, 0.0, 5], 2.53], ['N 12.0 mm E 0.0 mm at 150 km', [12.0, 0.0, 150], 4.33], ['N 0.05 mm E 0.08 mm at 25 km', [0.05, 0.08, 25], 0.7]], [['N 12.0 mm E 0.0 mm at 25 km', [12.0, 0.0, 25], 2.98], ['N 12.0 mm E 0.0 mm at 50 km', [12.0, 0.0, 50], 3.68], ['N 12.0 mm E 0.0 mm at 75 km', [12.0, 0.0, 75], 3.88], ['N 12.0 mm E 0.0 mm at 150 km', [12.0, 0.0, 150], 4.33], ['N 12.0 mm E 0.0 mm at 600 km', [12.0, 0.0, 600], 6.18], ['N 12.0 mm E 0.0 mm at 650 km', [12.0, 0.0, 650], None], ['N 0.0 mm E 0.0 mm at 5 km', [0.0, 0.0, 5], None], ['N 0.05 mm E 0.08 mm at 0 km', [0.05, 0.08, 0], 0.2]], [['N 0.0 mm E 0.0 mm at 5 km', [0.0, 0.0, 5], None], ['N 0.0 mm E 0.0 mm at 10 km', [0.0, 0.0, 10], None], ['N 0.0 mm E 0.0 mm at 25 km', [0.0, 0.0, 25], None], ['N 0.0 mm E 0.0 mm at 50 km', [0.0, 0.0, 50], None], ['N 0.0 mm E 0.0 mm at 75 km', [0.0, 0.0, 75], None], ['N 0.0 mm E 0.0 mm at 150 km', [0.0, 0.0, 150], None], ['N 0.0 mm E 0.0 mm at 600 km', [0.0, 0.0, 600], None], ['N 0.05 mm E 0.08 mm at 75 km', [0.05, 0.08, 75], 1.6]]]\nfor label, args, expected in fixtures[N - 1]:\n    check(label, solve(*args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"}},"limitations":"Stipulated deterministic teaching model of a seismological magnitude procedure; constants and tables are fixed by the contract and no claim of agency or standards conformance is made. This reproducer isolates one failure mechanism. Results cover the supplied fixtures. Variants within a family share a test contract and should remain grouped when constructing evaluation splits. Related mechanisms with a shared evaluation_group must also remain together; these controlled models are not independent production incidents.","method":"Deterministic executable model with adversarial boundary fixtures.","provenance":{"created_by":"Failure Map","dependencies":"Python standard library","family":"w2-seismic_magnitude_estimation-richter-a0-table-dead-channel-exclusion","generated_at":"2026-09-29T14:48:32.063543+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Classic ML reproduces Richter tables for historical catalogue homogenisation.","repair":"Exclude channels with zero amplitude.","root_cause":"A zero-amplitude channel is floored to 0.001 mm and averaged in.","sha256":"6da98a256a73eca505dd3ea8c5a0d9dc8d48b4feb6e51db3d6f1e199e7bf9398","title":"Richter -log A0 table magnitude: dead channel exclusion · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":39.092,"exit_code":1,"observations":[{"actual":1.4,"check":"N 1.0 mm E 1.0 mm at 0 km","expected":1.4,"passed":true},{"actual":1.45,"check":"N 1.0 mm E 1.0 mm at 5 km","expected":1.45,"passed":true},{"actual":1.5,"check":"N 1.0 mm E 1.0 mm at 10 km","expected":1.5,"passed":true},{"actual":1.9,"check":"N 1.0 mm E 1.0 mm at 25 km","expected":1.9,"passed":true},{"actual":2.6,"check":"N 1.0 mm E 1.0 mm at 50 km","expected":2.6,"passed":true},{"actual":2.8,"check":"N 1.0 mm E 1.0 mm at 75 km","expected":2.8,"passed":true},{"actual":2.48,"check":"N 12.0 mm E 0.0 mm at 0 km","expected":2.48,"passed":true},{"actual":null,"check":"N 0.05 mm E 0.08 mm at 5 km","expected":0.25,"passed":false}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"N 1.0 mm E 1.0 mm at 0 km\", \"actual\": 1.4, \"expected\": 1.4, \"passed\": true}, {\"check\": \"N 1.0 mm E 1.0 mm at 5 km\", \"actual\": 1.45, \"expected\": 1.45, \"passed\": true}, {\"check\": \"N 1.0 mm E 1.0 mm at 10 km\", \"actual\": 1.5, \"expected\": 1.5, \"passed\": true}, {\"check\": \"N 1.0 mm E 1.0 mm at 25 km\", \"actual\": 1.9, \"expected\": 1.9, \"passed\": true}, {\"check\": \"N 1.0 mm E 1.0 mm at 50 km\", \"actual\": 2.6, \"expected\": 2.6, \"passed\": true}, {\"check\": \"N 1.0 mm E 1.0 mm at 75 km\", \"actual\": 2.8, \"expected\": 2.8, \"passed\": true}, {\"check\": \"N 12.0 mm E 0.0 mm at 0 km\", \"actual\": 2.48, \"expected\": 2.48, \"passed\": true}, {\"check\": \"N 0.05 mm E 0.08 mm at 5 km\", \"actual\": null, \"expected\": 0.25, \"passed\": false}], \"passed\": false}\n"},"broken":{"elapsed_ms":37.58,"exit_code":1,"observations":[{"actual":1.4,"check":"N 1.0 mm E 1.0 mm at 0 km","expected":1.4,"passed":true},{"actual":1.45,"check":"N 1.0 mm E 1.0 mm at 5 km","expected":1.45,"passed":true},{"actual":1.5,"check":"N 1.0 mm E 1.0 mm at 10 km","expected":1.5,"passed":true},{"actual":1.9,"check":"N 1.0 mm E 1.0 mm at 25 km","expected":1.9,"passed":true},{"actual":2.6,"check":"N 1.0 mm E 1.0 mm at 50 km","expected":2.6,"passed":true},{"actual":2.8,"check":"N 1.0 mm E 1.0 mm at 75 km","expected":2.8,"passed":true},{"actual":0.44,"check":"N 12.0 mm E 0.0 mm at 0 km","expected":2.48,"passed":false},{"actual":0.25,"check":"N 0.05 mm E 0.08 mm at 5 km","expected":0.25,"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"N 1.0 mm E 1.0 mm at 0 km\", \"actual\": 1.4, \"expected\": 1.4, \"passed\": true}, {\"check\": \"N 1.0 mm E 1.0 mm at 5 km\", \"actual\": 1.45, \"expected\": 1.45, \"passed\": true}, {\"check\": \"N 1.0 mm E 1.0 mm at 10 km\", \"actual\": 1.5, \"expected\": 1.5, \"passed\": true}, {\"check\": \"N 1.0 mm E 1.0 mm at 25 km\", \"actual\": 1.9, \"expected\": 1.9, \"passed\": true}, {\"check\": \"N 1.0 mm E 1.0 mm at 50 km\", \"actual\": 2.6, \"expected\": 2.6, \"passed\": true}, {\"check\": \"N 1.0 mm E 1.0 mm at 75 km\", \"actual\": 2.8, \"expected\": 2.8, \"passed\": true}, {\"check\": \"N 12.0 mm E 0.0 mm at 0 km\", \"actual\": 0.44, \"expected\": 2.48, \"passed\": false}, {\"check\": \"N 0.05 mm E 0.08 mm at 5 km\", \"actual\": 0.25, \"expected\": 0.25, \"passed\": true}], \"passed\": false}\n"},"fixed":{"elapsed_ms":38.558,"exit_code":0,"observations":[{"actual":1.4,"check":"N 1.0 mm E 1.0 mm at 0 km","expected":1.4,"passed":true},{"actual":1.45,"check":"N 1.0 mm E 1.0 mm at 5 km","expected":1.45,"passed":true},{"actual":1.5,"check":"N 1.0 mm E 1.0 mm at 10 km","expected":1.5,"passed":true},{"actual":1.9,"check":"N 1.0 mm E 1.0 mm at 25 km","expected":1.9,"passed":true},{"actual":2.6,"check":"N 1.0 mm E 1.0 mm at 50 km","expected":2.6,"passed":true},{"actual":2.8,"check":"N 1.0 mm E 1.0 mm at 75 km","expected":2.8,"passed":true},{"actual":2.48,"check":"N 12.0 mm E 0.0 mm at 0 km","expected":2.48,"passed":true},{"actual":0.25,"check":"N 0.05 mm E 0.08 mm at 5 km","expected":0.25,"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"N 1.0 mm E 1.0 mm at 0 km\", \"actual\": 1.4, \"expected\": 1.4, \"passed\": true}, {\"check\": \"N 1.0 mm E 1.0 mm at 5 km\", \"actual\": 1.45, \"expected\": 1.45, \"passed\": true}, {\"check\": \"N 1.0 mm E 1.0 mm at 10 km\", \"actual\": 1.5, \"expected\": 1.5, \"passed\": true}, {\"check\": \"N 1.0 mm E 1.0 mm at 25 km\", \"actual\": 1.9, \"expected\": 1.9, \"passed\": true}, {\"check\": \"N 1.0 mm E 1.0 mm at 50 km\", \"actual\": 2.6, \"expected\": 2.6, \"passed\": true}, {\"check\": \"N 1.0 mm E 1.0 mm at 75 km\", \"actual\": 2.8, \"expected\": 2.8, \"passed\": true}, {\"check\": \"N 12.0 mm E 0.0 mm at 0 km\", \"actual\": 2.48, \"expected\": 2.48, \"passed\": true}, {\"check\": \"N 0.05 mm E 0.08 mm at 5 km\", \"actual\": 0.25, \"expected\": 0.25, \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}