{"abstract":"Settlement is a plain price average scaled by the divisor.","category":"Options payoff and settlement","checks":8,"contract":"Inputs components [weight, opening price or None, last close] and a divisor. Each component uses its opening price, or its last close if it did not open. Settlement = sum(weight*price)/divisor computed in Decimal and rounded half-up to cents. Return as a string.","evaluation_group":"w2-options_payoff_and_settlement-opening-settlement-value","failed_approach":"Weighting only components that opened leaves fallback prices unweighted.","family":"w2-options_payoff_and_settlement-opening-settlement-value-component-weighting","id":"FA-61586","implementations":{"attempt":{"sha256":"236d21148f7ca786f6690a594a4965b644a9f29d7e239b22fec3e3d61d4176bd","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nfrom decimal import Decimal, ROUND_HALF_UP, ROUND_HALF_EVEN, ROUND_DOWN\nN = 1\nobservations = []\ndef solve(components, divisor):\n    total = Decimal(0)\n    for w, op, close in components:\n        px = op if op is not None else close\n        total += (Decimal(str(w)) if op is not None else 1) * Decimal(str(px))\n    val = (total / Decimal(str(divisor))).quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)\n    return str(val)\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression component weighting 1', [[[3, 13.479, 12.986], [0.5, 161.37, 158.976], [0.5, 193.135, 197.081]], 8], '27.21'], ['regression component weighting 2', [[[3, 51.56, 53.295], [0.5, 174.778, 175.271], [2, None, 155.681]], 4], '138.36'], ['partial repair probe 1', [[[2, 117.299, 112.037], [0.5, None, 24.449]], 4], '61.71'], ['partial repair probe 2', [[[1.5, 136.595, 140.125], [2, None, 78.392], [1.5, 102.304, 98.119], [1.5, 106.144, 103.36], [1.5, 65.339, 68.752], [2, None, 149.232]], 0.5], '2141.64'], ['boundary control 1', [[[1, 10.005, 10.0]], 1], '10.01'], ['normal control 1', [[[1, 81.482, 82.869], [1, None, 60.357]], 1], '141.84'], ['normal control 2', [[[1, 66.523, 68.001], [1, 118.251, 120.993]], 2], '92.39'], ['normal control 3', [[[1, None, 88.977], [1, None, 49.669], [1, 68.444, 70.558], [1, 143.834, 140.092]], 8], '43.87']], [['regression component weighting 1', [[[3, 127.711, 129.547], [3, None, 97.406], [1.5, None, 128.005], [1.5, 108.974, 105.749], [1.5, None, 132.697], [2, 80.439, 81.276]], 1.25], '1112.59'], ['regression component weighting 2', [[[3, 19.347, 18.546], [3, 53.415, 51.55], [2, 62.823, 63.572], [1, 180.607, 184.998], [2, 116.252, 114.41]], 4], '189.26'], ['partial repair probe 1', [[[0.5, None, 88.66], [1.5, 110.336, 108.494]], 1], '209.83'], ['partial repair probe 2', [[[3, None, 154.303], [2, 111.662, 115.172], [0.5, None, 65.001], [2, 149.367, 155.124], [0.5, None, 11.233]], 0.5], '2046.17'], ['boundary control 1', [[[1, 10.005, 10.0]], 1], '10.01'], ['normal control 1', [[[1, 78.421, 79.525], [1, 179.157, 177.457]], 1], '257.58'], ['normal control 2', [[[1, None, 166.839], [1, 184.801, 188.328]], 8], '43.96'], ['normal control 3', [[[1, 166.869, 166.945], [1, 155.555, 154.795]], 0.5], '644.85']], [['regression component weighting 1', [[[2, 128.325, 134.42], [2, 70.639, 68.693], [3, None, 33.965], [2, None, 109.542], [2, 117.98, 116.309], [0.5, 15.763, 16.39]], 1.25], '770.20'], ['regression component weighting 2', [[[1, 16.248, 16.214], [0.5, 203.435, 198.134], [3, None, 58.341], [2, None, 139.181], [0.5, None, 29.931]], 2], '293.16'], ['partial repair probe 1', [[[3, 182.204, 176.361], [3, None, 65.618], [1.5, 68.079, 70.602], [1, None, 194.423]], 0.5], '2080.02'], ['partial repair probe 2', [[[2, 76.311, 79.686], [1.5, 134.131, 131.019], [3, None, 131.954], [1, None, 83.653], [0.5, None, 107.976]], 2], '443.66'], ['boundary control 1', [[[1, 10.005, 10.0]], 1], '10.01'], ['normal control 1', [[[1, None, 137.951], [1, None, 129.725], [1, 94.553, 90.269], [1, 84.63, 85.23], [1, None, 33.797]], 1], '480.66'], ['normal control 2', [[[1, 95.732, 99.548], [1, 10.24, 10.021]], 2], '52.99'], ['normal control 3', [[[1, 192.215, 195.95], [1, 26.3, 26.83]], 0.5], '437.03']], [['regression component weighting 1', [[[1, 153.045, 147.169], [1, 59.608, 59.609], [1, 162.952, 160.301], [1, 12.856, 13.271], [0.5, 24.004, 23.062]], 0.5], '800.93'], ['regression component weighting 2', [[[1.5, 37.724, 38.183], [1, 162.145, 159.23], [1.5, 196.22, 194.54]], 2], '256.53'], ['partial repair probe 1', [[[1, 18.793, 18.089], [0.5, 116.372, 112.157], [2, 32.811, 32.915], [1.5, None, 197.202]], 1.25], '350.72'], ['partial repair probe 2', [[[0.5, None, 47.219], [2, None, 175.641]], 1.25], '299.91'], ['boundary control 1', [[[1, 10.005, 10.0]], 1], '10.01'], ['normal control 1', [[[1, 20.872, 21.251], [1, None, 100.111]], 1], '120.98'], ['normal control 2', [[[1, 121.743, 124.99], [1, 17.002, 17.602]], 1], '138.75'], ['normal control 3', [[[1, 99.296, 100.215], [1, 188.519, 182.158]], 8], '35.98']], [['regression component weighting 1', [[[1, 208.403, 199.958], [3, 141.132, 144.086], [2, 48.774, 48.99], [2, None, 48.807], [3, None, 121.457]], 4], '297.83'], ['regression component weighting 2', [[[1.5, 62.219, 62.373], [1, 193.83, 198.269]], 4], '71.79'], ['partial repair probe 1', [[[1.5, None, 80.916], [1, 12.21, 11.683], [0.5, 154.941, 151.005], [1, 39.42, 39.707]], 0.5], '500.95'], ['partial repair probe 2', [[[1.5, None, 189.456], [2, 126.608, 131.279], [0.5, 191.182, 192.847], [2, None, 32.658], [1.5, 122.29, 125.114]], 2], '440.87'], ['boundary control 1', [[[1, 10.005, 10.0]], 1], '10.01'], ['normal control 1', [[[1, 76.249, 73.412], [1, 146.143, 141.273], [1, None, 26.499]], 2], '124.45'], ['normal control 2', [[[1, 139.48, 138.297], [1, 149.017, 145.959]], 4], '72.12'], ['normal control 3', [[[1, None, 180.47], [1, 83.49, 85.396]], 0.5], '527.92']]]\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":"b6bc247723240353ac63e92693d225a93ee3e116177000c0530be698bf05d6e9","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nfrom decimal import Decimal, ROUND_HALF_UP, ROUND_HALF_EVEN, ROUND_DOWN\nN = 1\nobservations = []\ndef solve(components, divisor):\n    total = Decimal(0)\n    for w, op, close in components:\n        px = op if op is not None else close\n        total += Decimal(str(px))\n    val = (total / Decimal(str(divisor))).quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)\n    return str(val)\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression component weighting 1', [[[3, 13.479, 12.986], [0.5, 161.37, 158.976], [0.5, 193.135, 197.081]], 8], '27.21'], ['regression component weighting 2', [[[3, 51.56, 53.295], [0.5, 174.778, 175.271], [2, None, 155.681]], 4], '138.36'], ['partial repair probe 1', [[[2, 117.299, 112.037], [0.5, None, 24.449]], 4], '61.71'], ['partial repair probe 2', [[[1.5, 136.595, 140.125], [2, None, 78.392], [1.5, 102.304, 98.119], [1.5, 106.144, 103.36], [1.5, 65.339, 68.752], [2, None, 149.232]], 0.5], '2141.64'], ['boundary control 1', [[[1, 10.005, 10.0]], 1], '10.01'], ['normal control 1', [[[1, 81.482, 82.869], [1, None, 60.357]], 1], '141.84'], ['normal control 2', [[[1, 66.523, 68.001], [1, 118.251, 120.993]], 2], '92.39'], ['normal control 3', [[[1, None, 88.977], [1, None, 49.669], [1, 68.444, 70.558], [1, 143.834, 140.092]], 8], '43.87']], [['regression component weighting 1', [[[3, 127.711, 129.547], [3, None, 97.406], [1.5, None, 128.005], [1.5, 108.974, 105.749], [1.5, None, 132.697], [2, 80.439, 81.276]], 1.25], '1112.59'], ['regression component weighting 2', [[[3, 19.347, 18.546], [3, 53.415, 51.55], [2, 62.823, 63.572], [1, 180.607, 184.998], [2, 116.252, 114.41]], 4], '189.26'], ['partial repair probe 1', [[[0.5, None, 88.66], [1.5, 110.336, 108.494]], 1], '209.83'], ['partial repair probe 2', [[[3, None, 154.303], [2, 111.662, 115.172], [0.5, None, 65.001], [2, 149.367, 155.124], [0.5, None, 11.233]], 0.5], '2046.17'], ['boundary control 1', [[[1, 10.005, 10.0]], 1], '10.01'], ['normal control 1', [[[1, 78.421, 79.525], [1, 179.157, 177.457]], 1], '257.58'], ['normal control 2', [[[1, None, 166.839], [1, 184.801, 188.328]], 8], '43.96'], ['normal control 3', [[[1, 166.869, 166.945], [1, 155.555, 154.795]], 0.5], '644.85']], [['regression component weighting 1', [[[2, 128.325, 134.42], [2, 70.639, 68.693], [3, None, 33.965], [2, None, 109.542], [2, 117.98, 116.309], [0.5, 15.763, 16.39]], 1.25], '770.20'], ['regression component weighting 2', [[[1, 16.248, 16.214], [0.5, 203.435, 198.134], [3, None, 58.341], [2, None, 139.181], [0.5, None, 29.931]], 2], '293.16'], ['partial repair probe 1', [[[3, 182.204, 176.361], [3, None, 65.618], [1.5, 68.079, 70.602], [1, None, 194.423]], 0.5], '2080.02'], ['partial repair probe 2', [[[2, 76.311, 79.686], [1.5, 134.131, 131.019], [3, None, 131.954], [1, None, 83.653], [0.5, None, 107.976]], 2], '443.66'], ['boundary control 1', [[[1, 10.005, 10.0]], 1], '10.01'], ['normal control 1', [[[1, None, 137.951], [1, None, 129.725], [1, 94.553, 90.269], [1, 84.63, 85.23], [1, None, 33.797]], 1], '480.66'], ['normal control 2', [[[1, 95.732, 99.548], [1, 10.24, 10.021]], 2], '52.99'], ['normal control 3', [[[1, 192.215, 195.95], [1, 26.3, 26.83]], 0.5], '437.03']], [['regression component weighting 1', [[[1, 153.045, 147.169], [1, 59.608, 59.609], [1, 162.952, 160.301], [1, 12.856, 13.271], [0.5, 24.004, 23.062]], 0.5], '800.93'], ['regression component weighting 2', [[[1.5, 37.724, 38.183], [1, 162.145, 159.23], [1.5, 196.22, 194.54]], 2], '256.53'], ['partial repair probe 1', [[[1, 18.793, 18.089], [0.5, 116.372, 112.157], [2, 32.811, 32.915], [1.5, None, 197.202]], 1.25], '350.72'], ['partial repair probe 2', [[[0.5, None, 47.219], [2, None, 175.641]], 1.25], '299.91'], ['boundary control 1', [[[1, 10.005, 10.0]], 1], '10.01'], ['normal control 1', [[[1, 20.872, 21.251], [1, None, 100.111]], 1], '120.98'], ['normal control 2', [[[1, 121.743, 124.99], [1, 17.002, 17.602]], 1], '138.75'], ['normal control 3', [[[1, 99.296, 100.215], [1, 188.519, 182.158]], 8], '35.98']], [['regression component weighting 1', [[[1, 208.403, 199.958], [3, 141.132, 144.086], [2, 48.774, 48.99], [2, None, 48.807], [3, None, 121.457]], 4], '297.83'], ['regression component weighting 2', [[[1.5, 62.219, 62.373], [1, 193.83, 198.269]], 4], '71.79'], ['partial repair probe 1', [[[1.5, None, 80.916], [1, 12.21, 11.683], [0.5, 154.941, 151.005], [1, 39.42, 39.707]], 0.5], '500.95'], ['partial repair probe 2', [[[1.5, None, 189.456], [2, 126.608, 131.279], [0.5, 191.182, 192.847], [2, None, 32.658], [1.5, 122.29, 125.114]], 2], '440.87'], ['boundary control 1', [[[1, 10.005, 10.0]], 1], '10.01'], ['normal control 1', [[[1, 76.249, 73.412], [1, 146.143, 141.273], [1, None, 26.499]], 2], '124.45'], ['normal control 2', [[[1, 139.48, 138.297], [1, 149.017, 145.959]], 4], '72.12'], ['normal control 3', [[[1, None, 180.47], [1, 83.49, 85.396]], 0.5], '527.92']]]\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":"38d8ac81b20961ad6b9737908fd8b63c202494ca4ef6732d28b0b71312fd5483","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nfrom decimal import Decimal, ROUND_HALF_UP, ROUND_HALF_EVEN, ROUND_DOWN\nN = 1\nobservations = []\ndef solve(components, divisor):\n    total = Decimal(0)\n    for w, op, close in components:\n        px = op if op is not None else close\n        total += Decimal(str(w)) * Decimal(str(px))\n    val = (total / Decimal(str(divisor))).quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)\n    return str(val)\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression component weighting 1', [[[3, 13.479, 12.986], [0.5, 161.37, 158.976], [0.5, 193.135, 197.081]], 8], '27.21'], ['regression component weighting 2', [[[3, 51.56, 53.295], [0.5, 174.778, 175.271], [2, None, 155.681]], 4], '138.36'], ['partial repair probe 1', [[[2, 117.299, 112.037], [0.5, None, 24.449]], 4], '61.71'], ['partial repair probe 2', [[[1.5, 136.595, 140.125], [2, None, 78.392], [1.5, 102.304, 98.119], [1.5, 106.144, 103.36], [1.5, 65.339, 68.752], [2, None, 149.232]], 0.5], '2141.64'], ['boundary control 1', [[[1, 10.005, 10.0]], 1], '10.01'], ['normal control 1', [[[1, 81.482, 82.869], [1, None, 60.357]], 1], '141.84'], ['normal control 2', [[[1, 66.523, 68.001], [1, 118.251, 120.993]], 2], '92.39'], ['normal control 3', [[[1, None, 88.977], [1, None, 49.669], [1, 68.444, 70.558], [1, 143.834, 140.092]], 8], '43.87']], [['regression component weighting 1', [[[3, 127.711, 129.547], [3, None, 97.406], [1.5, None, 128.005], [1.5, 108.974, 105.749], [1.5, None, 132.697], [2, 80.439, 81.276]], 1.25], '1112.59'], ['regression component weighting 2', [[[3, 19.347, 18.546], [3, 53.415, 51.55], [2, 62.823, 63.572], [1, 180.607, 184.998], [2, 116.252, 114.41]], 4], '189.26'], ['partial repair probe 1', [[[0.5, None, 88.66], [1.5, 110.336, 108.494]], 1], '209.83'], ['partial repair probe 2', [[[3, None, 154.303], [2, 111.662, 115.172], [0.5, None, 65.001], [2, 149.367, 155.124], [0.5, None, 11.233]], 0.5], '2046.17'], ['boundary control 1', [[[1, 10.005, 10.0]], 1], '10.01'], ['normal control 1', [[[1, 78.421, 79.525], [1, 179.157, 177.457]], 1], '257.58'], ['normal control 2', [[[1, None, 166.839], [1, 184.801, 188.328]], 8], '43.96'], ['normal control 3', [[[1, 166.869, 166.945], [1, 155.555, 154.795]], 0.5], '644.85']], [['regression component weighting 1', [[[2, 128.325, 134.42], [2, 70.639, 68.693], [3, None, 33.965], [2, None, 109.542], [2, 117.98, 116.309], [0.5, 15.763, 16.39]], 1.25], '770.20'], ['regression component weighting 2', [[[1, 16.248, 16.214], [0.5, 203.435, 198.134], [3, None, 58.341], [2, None, 139.181], [0.5, None, 29.931]], 2], '293.16'], ['partial repair probe 1', [[[3, 182.204, 176.361], [3, None, 65.618], [1.5, 68.079, 70.602], [1, None, 194.423]], 0.5], '2080.02'], ['partial repair probe 2', [[[2, 76.311, 79.686], [1.5, 134.131, 131.019], [3, None, 131.954], [1, None, 83.653], [0.5, None, 107.976]], 2], '443.66'], ['boundary control 1', [[[1, 10.005, 10.0]], 1], '10.01'], ['normal control 1', [[[1, None, 137.951], [1, None, 129.725], [1, 94.553, 90.269], [1, 84.63, 85.23], [1, None, 33.797]], 1], '480.66'], ['normal control 2', [[[1, 95.732, 99.548], [1, 10.24, 10.021]], 2], '52.99'], ['normal control 3', [[[1, 192.215, 195.95], [1, 26.3, 26.83]], 0.5], '437.03']], [['regression component weighting 1', [[[1, 153.045, 147.169], [1, 59.608, 59.609], [1, 162.952, 160.301], [1, 12.856, 13.271], [0.5, 24.004, 23.062]], 0.5], '800.93'], ['regression component weighting 2', [[[1.5, 37.724, 38.183], [1, 162.145, 159.23], [1.5, 196.22, 194.54]], 2], '256.53'], ['partial repair probe 1', [[[1, 18.793, 18.089], [0.5, 116.372, 112.157], [2, 32.811, 32.915], [1.5, None, 197.202]], 1.25], '350.72'], ['partial repair probe 2', [[[0.5, None, 47.219], [2, None, 175.641]], 1.25], '299.91'], ['boundary control 1', [[[1, 10.005, 10.0]], 1], '10.01'], ['normal control 1', [[[1, 20.872, 21.251], [1, None, 100.111]], 1], '120.98'], ['normal control 2', [[[1, 121.743, 124.99], [1, 17.002, 17.602]], 1], '138.75'], ['normal control 3', [[[1, 99.296, 100.215], [1, 188.519, 182.158]], 8], '35.98']], [['regression component weighting 1', [[[1, 208.403, 199.958], [3, 141.132, 144.086], [2, 48.774, 48.99], [2, None, 48.807], [3, None, 121.457]], 4], '297.83'], ['regression component weighting 2', [[[1.5, 62.219, 62.373], [1, 193.83, 198.269]], 4], '71.79'], ['partial repair probe 1', [[[1.5, None, 80.916], [1, 12.21, 11.683], [0.5, 154.941, 151.005], [1, 39.42, 39.707]], 0.5], '500.95'], ['partial repair probe 2', [[[1.5, None, 189.456], [2, 126.608, 131.279], [0.5, 191.182, 192.847], [2, None, 32.658], [1.5, 122.29, 125.114]], 2], '440.87'], ['boundary control 1', [[[1, 10.005, 10.0]], 1], '10.01'], ['normal control 1', [[[1, 76.249, 73.412], [1, 146.143, 141.273], [1, None, 26.499]], 2], '124.45'], ['normal control 2', [[[1, 139.48, 138.297], [1, 149.017, 145.959]], 4], '72.12'], ['normal control 3', [[[1, None, 180.47], [1, 83.49, 85.396]], 0.5], '527.92']]]\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":"A deterministic toy contract stated explicitly in the contract field; no claim of conformance to any exchange or clearing rulebook. 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-options_payoff_and_settlement-opening-settlement-value-component-weighting","generated_at":"2026-09-29T14:46:56.700161+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Option expiry, exercise and settlement engines move cash and shares; a wrong branch misstates obligations.","repair":"Multiply each price by its weight.","root_cause":"Prices are summed without their weights.","sha256":"2ed0ce7b20f94b705fc5f8c2a80024b051b2b3f512ae0993614274e7c8878057","title":"Special opening settlement value for index options: component weights are ignored · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":41.136,"exit_code":1,"observations":[{"actual":"27.21","check":"regression component weighting 1","expected":"27.21","passed":true},{"actual":"99.44","check":"regression component weighting 2","expected":"138.36","passed":false},{"actual":"64.76","check":"partial repair probe 1","expected":"61.71","passed":false},{"actual":"1686.39","check":"partial repair probe 2","expected":"2141.64","passed":false},{"actual":"10.01","check":"boundary control 1","expected":"10.01","passed":true},{"actual":"141.84","check":"normal control 1","expected":"141.84","passed":true},{"actual":"92.39","check":"normal control 2","expected":"92.39","passed":true},{"actual":"43.87","check":"normal control 3","expected":"43.87","passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression component weighting 1\", \"actual\": \"27.21\", \"expected\": \"27.21\", \"passed\": true}, {\"check\": \"regression component weighting 2\", \"actual\": \"99.44\", \"expected\": \"138.36\", \"passed\": false}, {\"check\": \"partial repair probe 1\", \"actual\": \"64.76\", \"expected\": \"61.71\", \"passed\": false}, {\"check\": \"partial repair probe 2\", \"actual\": \"1686.39\", \"expected\": \"2141.64\", \"passed\": false}, {\"check\": \"boundary control 1\", \"actual\": \"10.01\", \"expected\": \"10.01\", \"passed\": true}, {\"check\": \"normal control 1\", \"actual\": \"141.84\", \"expected\": \"141.84\", \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": \"92.39\", \"expected\": \"92.39\", \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": \"43.87\", \"expected\": \"43.87\", \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":44.187,"exit_code":1,"observations":[{"actual":"46.00","check":"regression component weighting 1","expected":"27.21","passed":false},{"actual":"95.50","check":"regression component weighting 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