{"abstract":"Vaccine failures vanish from the population.","category":"Epidemic compartment models","checks":7,"contract":"Each day from day index start_day (inclusive), dose=min(doses_per_day, S) is given to susceptibles before transmission; dose*efficacy moves S->V; failed vaccinees stay in S; mixing uses the full pop; return [S, I, R, V, doses administered] rounded to 3.","evaluation_group":"w2-epidemic-vaccine-campaign","failed_approach":"Removing the failure fraction from S inverts the all-or-nothing rule.","family":"w2-epidemic-vaccine-campaign-efficacy-application","id":"FA-65071","implementations":{"attempt":{"sha256":"e069dc0617370a3836131c3e32c5713e31faddceaeff5aa0f0e366ec8f2e210c","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport math\nN = 1\nobservations = []\ndef solve(beta, gamma, pop, i0, doses_per_day, start_day, efficacy, days):\n    s, i, r, v = float(pop - i0), float(i0), 0.0, 0.0\n    given = 0.0\n    for day in range(days):\n        if day >= start_day:\n            dose = min(doses_per_day, s)\n            s -= dose * (1 - efficacy)\n            v += dose * efficacy\n            given += dose\n        inf = beta * s * i / pop\n        rec = gamma * i\n        s -= inf\n        i += inf - rec\n        r += rec\n    return [round(s, 3), round(i, 3), round(r, 3), round(v, 3), round(given, 3)]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: city campaign from day 5',\n   (0.4, 0.2, 10000, 20, 200, 5, 0.9, 30),\n   [4007.174, 324.024, 1168.803, 4500.0, 5000.0]),\n  ('regression: campaign from day 0',\n   (0.5, 0.25, 2000, 10, 50, 0, 0.8, 20),\n   [872.113, 79.727, 248.159, 800.0, 1000.0]),\n  ('regression: supply exceeds susceptibles',\n   (0.3, 0.1, 100, 2, 80, 1, 0.95, 6),\n   [0.0, 1.516, 1.233, 97.251, 102.369]),\n  ('control: late campaign never starts',\n   (0.3, 0.1, 1000, 5, 100, 50, 0.9, 20),\n   [777.374, 141.242, 81.385, 0.0, 0.0]),\n  ('regression: perfect vaccine small town',\n   (0.6, 0.2, 500, 5, 40, 2, 1.0, 15),\n   [0.0, 10.271, 55.609, 434.12, 434.12]),\n  ('regression: poor vaccine',\n   (0.45, 0.15, 3000, 30, 150, 3, 0.4, 25),\n   [237.471, 307.647, 1134.882, 1320.0, 3300.0]),\n  ('control: no doses', (0.4, 0.2, 1000, 10, 0, 0, 0.9, 10), [896.73, 54.094, 49.176, 0.0, 0.0])],\n [('regression: city campaign from day 5',\n   (0.4, 0.2, 10000, 20, 200, 5, 0.9, 30),\n   [4007.174, 324.024, 1168.803, 4500.0, 5000.0]),\n  ('regression: campaign from day 0',\n   (0.5, 0.25, 2000, 10, 50, 0, 0.8, 20),\n   [872.113, 79.727, 248.159, 800.0, 1000.0]),\n  ('control: late campaign never starts',\n   (0.3, 0.1, 1000, 5, 100, 50, 0.9, 20),\n   [777.374, 141.242, 81.385, 0.0, 0.0]),\n  ('regression: perfect vaccine small town',\n   (0.6, 0.2, 500, 5, 40, 2, 1.0, 15),\n   [0.0, 10.271, 55.609, 434.12, 434.12]),\n  ('regression: poor vaccine',\n   (0.45, 0.15, 3000, 30, 150, 3, 0.4, 25),\n   [237.471, 307.647, 1134.882, 1320.0, 3300.0]),\n  ('control: no doses', (0.4, 0.2, 1000, 10, 0, 0, 0.9, 10), [896.73, 54.094, 49.176, 0.0, 0.0]),\n  ('regression: start day one', (0.35, 0.1, 800, 4, 30, 1, 0.7, 12), [519.85, 32.463, 16.687, 231.0, 330.0])],\n [('regression: city campaign from day 5',\n   (0.4, 0.2, 10000, 20, 200, 5, 0.9, 30),\n   [4007.174, 324.024, 1168.803, 4500.0, 5000.0]),\n  ('regression: campaign from day 0',\n   (0.5, 0.25, 2000, 10, 50, 0, 0.8, 20),\n   [872.113, 79.727, 248.159, 800.0, 1000.0]),\n  ('regression: supply exceeds susceptibles',\n   (0.3, 0.1, 100, 2, 80, 1, 0.95, 6),\n   [0.0, 1.516, 1.233, 97.251, 102.369]),\n  ('control: late campaign never starts',\n   (0.3, 0.1, 1000, 5, 100, 50, 0.9, 20),\n   [777.374, 141.242, 81.385, 0.0, 0.0]),\n  ('regression: perfect vaccine small town',\n   (0.6, 0.2, 500, 5, 40, 2, 1.0, 15),\n   [0.0, 10.271, 55.609, 434.12, 434.12]),\n  ('control: no doses', (0.4, 0.2, 1000, 10, 0, 0, 0.9, 10), [896.73, 54.094, 49.176, 0.0, 0.0]),\n  ('regression: start day one', (0.35, 0.1, 800, 4, 30, 1, 0.7, 12), [519.85, 32.463, 16.687, 231.0, 330.0])],\n [('regression: campaign from day 0',\n   (0.5, 0.25, 2000, 10, 50, 0, 0.8, 20),\n   [872.113, 79.727, 248.159, 800.0, 1000.0]),\n  ('regression: supply exceeds susceptibles',\n   (0.3, 0.1, 100, 2, 80, 1, 0.95, 6),\n   [0.0, 1.516, 1.233, 97.251, 102.369]),\n  ('control: late campaign never starts',\n   (0.3, 0.1, 1000, 5, 100, 50, 0.9, 20),\n   [777.374, 141.242, 81.385, 0.0, 0.0]),\n  ('regression: perfect vaccine small town',\n   (0.6, 0.2, 500, 5, 40, 2, 1.0, 15),\n   [0.0, 10.271, 55.609, 434.12, 434.12]),\n  ('regression: poor vaccine',\n   (0.45, 0.15, 3000, 30, 150, 3, 0.4, 25),\n   [237.471, 307.647, 1134.882, 1320.0, 3300.0]),\n  ('control: no doses', (0.4, 0.2, 1000, 10, 0, 0, 0.9, 10), [896.73, 54.094, 49.176, 0.0, 0.0]),\n  ('regression: start day one', (0.35, 0.1, 800, 4, 30, 1, 0.7, 12), [519.85, 32.463, 16.687, 231.0, 330.0])],\n [('regression: city campaign from day 5',\n   (0.4, 0.2, 10000, 20, 200, 5, 0.9, 30),\n   [4007.174, 324.024, 1168.803, 4500.0, 5000.0]),\n  ('regression: campaign from day 0',\n   (0.5, 0.25, 2000, 10, 50, 0, 0.8, 20),\n   [872.113, 79.727, 248.159, 800.0, 1000.0]),\n  ('control: late campaign never starts',\n   (0.3, 0.1, 1000, 5, 100, 50, 0.9, 20),\n   [777.374, 141.242, 81.385, 0.0, 0.0]),\n  ('regression: perfect vaccine small town',\n   (0.6, 0.2, 500, 5, 40, 2, 1.0, 15),\n   [0.0, 10.271, 55.609, 434.12, 434.12]),\n  ('regression: poor vaccine',\n   (0.45, 0.15, 3000, 30, 150, 3, 0.4, 25),\n   [237.471, 307.647, 1134.882, 1320.0, 3300.0]),\n  ('control: no doses', (0.4, 0.2, 1000, 10, 0, 0, 0.9, 10), [896.73, 54.094, 49.176, 0.0, 0.0]),\n  ('regression: start day one', (0.35, 0.1, 800, 4, 30, 1, 0.7, 12), [519.85, 32.463, 16.687, 231.0, 330.0])]]\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":"1a35cb629789ece00b9d4c4a619ae082f87b6382122c7f6f05fdaf0c9d828234","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport math\nN = 1\nobservations = []\ndef solve(beta, gamma, pop, i0, doses_per_day, start_day, efficacy, days):\n    s, i, r, v = float(pop - i0), float(i0), 0.0, 0.0\n    given = 0.0\n    for day in range(days):\n        if day >= start_day:\n            dose = min(doses_per_day, s)\n            s -= dose\n            v += dose * efficacy\n            given += dose\n        inf = beta * s * i / pop\n        rec = gamma * i\n        s -= inf\n        i += inf - rec\n        r += rec\n    return [round(s, 3), round(i, 3), round(r, 3), round(v, 3), round(given, 3)]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: city campaign from day 5',\n   (0.4, 0.2, 10000, 20, 200, 5, 0.9, 30),\n   [4007.174, 324.024, 1168.803, 4500.0, 5000.0]),\n  ('regression: campaign from day 0',\n   (0.5, 0.25, 2000, 10, 50, 0, 0.8, 20),\n   [872.113, 79.727, 248.159, 800.0, 1000.0]),\n  ('regression: supply exceeds susceptibles',\n   (0.3, 0.1, 100, 2, 80, 1, 0.95, 6),\n   [0.0, 1.516, 1.233, 97.251, 102.369]),\n  ('control: late campaign never starts',\n   (0.3, 0.1, 1000, 5, 100, 50, 0.9, 20),\n   [777.374, 141.242, 81.385, 0.0, 0.0]),\n  ('regression: perfect vaccine small town',\n   (0.6, 0.2, 500, 5, 40, 2, 1.0, 15),\n   [0.0, 10.271, 55.609, 434.12, 434.12]),\n  ('regression: poor vaccine',\n   (0.45, 0.15, 3000, 30, 150, 3, 0.4, 25),\n   [237.471, 307.647, 1134.882, 1320.0, 3300.0]),\n  ('control: no doses', (0.4, 0.2, 1000, 10, 0, 0, 0.9, 10), [896.73, 54.094, 49.176, 0.0, 0.0])],\n [('regression: city campaign from day 5',\n   (0.4, 0.2, 10000, 20, 200, 5, 0.9, 30),\n   [4007.174, 324.024, 1168.803, 4500.0, 5000.0]),\n  ('regression: campaign from day 0',\n   (0.5, 0.25, 2000, 10, 50, 0, 0.8, 20),\n   [872.113, 79.727, 248.159, 800.0, 1000.0]),\n  ('control: late campaign never starts',\n   (0.3, 0.1, 1000, 5, 100, 50, 0.9, 20),\n   [777.374, 141.242, 81.385, 0.0, 0.0]),\n  ('regression: perfect vaccine small town',\n   (0.6, 0.2, 500, 5, 40, 2, 1.0, 15),\n   [0.0, 10.271, 55.609, 434.12, 434.12]),\n  ('regression: poor vaccine',\n   (0.45, 0.15, 3000, 30, 150, 3, 0.4, 25),\n   [237.471, 307.647, 1134.882, 1320.0, 3300.0]),\n  ('control: no doses', (0.4, 0.2, 1000, 10, 0, 0, 0.9, 10), [896.73, 54.094, 49.176, 0.0, 0.0]),\n  ('regression: start day one', (0.35, 0.1, 800, 4, 30, 1, 0.7, 12), [519.85, 32.463, 16.687, 231.0, 330.0])],\n [('regression: city campaign from day 5',\n   (0.4, 0.2, 10000, 20, 200, 5, 0.9, 30),\n   [4007.174, 324.024, 1168.803, 4500.0, 5000.0]),\n  ('regression: campaign from day 0',\n   (0.5, 0.25, 2000, 10, 50, 0, 0.8, 20),\n   [872.113, 79.727, 248.159, 800.0, 1000.0]),\n  ('regression: supply exceeds susceptibles',\n   (0.3, 0.1, 100, 2, 80, 1, 0.95, 6),\n   [0.0, 1.516, 1.233, 97.251, 102.369]),\n  ('control: late campaign never starts',\n   (0.3, 0.1, 1000, 5, 100, 50, 0.9, 20),\n   [777.374, 141.242, 81.385, 0.0, 0.0]),\n  ('regression: perfect vaccine small town',\n   (0.6, 0.2, 500, 5, 40, 2, 1.0, 15),\n   [0.0, 10.271, 55.609, 434.12, 434.12]),\n  ('control: no doses', (0.4, 0.2, 1000, 10, 0, 0, 0.9, 10), [896.73, 54.094, 49.176, 0.0, 0.0]),\n  ('regression: start day one', (0.35, 0.1, 800, 4, 30, 1, 0.7, 12), [519.85, 32.463, 16.687, 231.0, 330.0])],\n [('regression: campaign from day 0',\n   (0.5, 0.25, 2000, 10, 50, 0, 0.8, 20),\n   [872.113, 79.727, 248.159, 800.0, 1000.0]),\n  ('regression: supply exceeds susceptibles',\n   (0.3, 0.1, 100, 2, 80, 1, 0.95, 6),\n   [0.0, 1.516, 1.233, 97.251, 102.369]),\n  ('control: late campaign never starts',\n   (0.3, 0.1, 1000, 5, 100, 50, 0.9, 20),\n   [777.374, 141.242, 81.385, 0.0, 0.0]),\n  ('regression: perfect vaccine small town',\n   (0.6, 0.2, 500, 5, 40, 2, 1.0, 15),\n   [0.0, 10.271, 55.609, 434.12, 434.12]),\n  ('regression: poor vaccine',\n   (0.45, 0.15, 3000, 30, 150, 3, 0.4, 25),\n   [237.471, 307.647, 1134.882, 1320.0, 3300.0]),\n  ('control: no doses', (0.4, 0.2, 1000, 10, 0, 0, 0.9, 10), [896.73, 54.094, 49.176, 0.0, 0.0]),\n  ('regression: start day one', (0.35, 0.1, 800, 4, 30, 1, 0.7, 12), [519.85, 32.463, 16.687, 231.0, 330.0])],\n [('regression: city campaign from day 5',\n   (0.4, 0.2, 10000, 20, 200, 5, 0.9, 30),\n   [4007.174, 324.024, 1168.803, 4500.0, 5000.0]),\n  ('regression: campaign from day 0',\n   (0.5, 0.25, 2000, 10, 50, 0, 0.8, 20),\n   [872.113, 79.727, 248.159, 800.0, 1000.0]),\n  ('control: late campaign never starts',\n   (0.3, 0.1, 1000, 5, 100, 50, 0.9, 20),\n   [777.374, 141.242, 81.385, 0.0, 0.0]),\n  ('regression: perfect vaccine small town',\n   (0.6, 0.2, 500, 5, 40, 2, 1.0, 15),\n   [0.0, 10.271, 55.609, 434.12, 434.12]),\n  ('regression: poor vaccine',\n   (0.45, 0.15, 3000, 30, 150, 3, 0.4, 25),\n   [237.471, 307.647, 1134.882, 1320.0, 3300.0]),\n  ('control: no doses', (0.4, 0.2, 1000, 10, 0, 0, 0.9, 10), [896.73, 54.094, 49.176, 0.0, 0.0]),\n  ('regression: start day one', (0.35, 0.1, 800, 4, 30, 1, 0.7, 12), [519.85, 32.463, 16.687, 231.0, 330.0])]]\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":"a8f168ad0533278fef5a4231d60edd19c88f20da1fd4fe9e504a20593a3e33e8","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport math\nN = 1\nobservations = []\ndef solve(beta, gamma, pop, i0, doses_per_day, start_day, efficacy, days):\n    s, i, r, v = float(pop - i0), float(i0), 0.0, 0.0\n    given = 0.0\n    for day in range(days):\n        if day >= start_day:\n            dose = min(doses_per_day, s)\n            s -= dose * efficacy\n            v += dose * efficacy\n            given += dose\n        inf = beta * s * i / pop\n        rec = gamma * i\n        s -= inf\n        i += inf - rec\n        r += rec\n    return [round(s, 3), round(i, 3), round(r, 3), round(v, 3), round(given, 3)]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: city campaign from day 5',\n   (0.4, 0.2, 10000, 20, 200, 5, 0.9, 30),\n   [4007.174, 324.024, 1168.803, 4500.0, 5000.0]),\n  ('regression: campaign from day 0',\n   (0.5, 0.25, 2000, 10, 50, 0, 0.8, 20),\n   [872.113, 79.727, 248.159, 800.0, 1000.0]),\n  ('regression: supply exceeds susceptibles',\n   (0.3, 0.1, 100, 2, 80, 1, 0.95, 6),\n   [0.0, 1.516, 1.233, 97.251, 102.369]),\n  ('control: late campaign never starts',\n   (0.3, 0.1, 1000, 5, 100, 50, 0.9, 20),\n   [777.374, 141.242, 81.385, 0.0, 0.0]),\n  ('regression: perfect vaccine small town',\n   (0.6, 0.2, 500, 5, 40, 2, 1.0, 15),\n   [0.0, 10.271, 55.609, 434.12, 434.12]),\n  ('regression: poor vaccine',\n   (0.45, 0.15, 3000, 30, 150, 3, 0.4, 25),\n   [237.471, 307.647, 1134.882, 1320.0, 3300.0]),\n  ('control: no doses', (0.4, 0.2, 1000, 10, 0, 0, 0.9, 10), [896.73, 54.094, 49.176, 0.0, 0.0])],\n [('regression: city campaign from day 5',\n   (0.4, 0.2, 10000, 20, 200, 5, 0.9, 30),\n   [4007.174, 324.024, 1168.803, 4500.0, 5000.0]),\n  ('regression: campaign from day 0',\n   (0.5, 0.25, 2000, 10, 50, 0, 0.8, 20),\n   [872.113, 79.727, 248.159, 800.0, 1000.0]),\n  ('control: late campaign never starts',\n   (0.3, 0.1, 1000, 5, 100, 50, 0.9, 20),\n   [777.374, 141.242, 81.385, 0.0, 0.0]),\n  ('regression: perfect vaccine small town',\n   (0.6, 0.2, 500, 5, 40, 2, 1.0, 15),\n   [0.0, 10.271, 55.609, 434.12, 434.12]),\n  ('regression: poor vaccine',\n   (0.45, 0.15, 3000, 30, 150, 3, 0.4, 25),\n   [237.471, 307.647, 1134.882, 1320.0, 3300.0]),\n  ('control: no doses', (0.4, 0.2, 1000, 10, 0, 0, 0.9, 10), [896.73, 54.094, 49.176, 0.0, 0.0]),\n  ('regression: start day one', (0.35, 0.1, 800, 4, 30, 1, 0.7, 12), [519.85, 32.463, 16.687, 231.0, 330.0])],\n [('regression: city campaign from day 5',\n   (0.4, 0.2, 10000, 20, 200, 5, 0.9, 30),\n   [4007.174, 324.024, 1168.803, 4500.0, 5000.0]),\n  ('regression: campaign from day 0',\n   (0.5, 0.25, 2000, 10, 50, 0, 0.8, 20),\n   [872.113, 79.727, 248.159, 800.0, 1000.0]),\n  ('regression: supply exceeds susceptibles',\n   (0.3, 0.1, 100, 2, 80, 1, 0.95, 6),\n   [0.0, 1.516, 1.233, 97.251, 102.369]),\n  ('control: late campaign never starts',\n   (0.3, 0.1, 1000, 5, 100, 50, 0.9, 20),\n   [777.374, 141.242, 81.385, 0.0, 0.0]),\n  ('regression: perfect vaccine small town',\n   (0.6, 0.2, 500, 5, 40, 2, 1.0, 15),\n   [0.0, 10.271, 55.609, 434.12, 434.12]),\n  ('control: no doses', (0.4, 0.2, 1000, 10, 0, 0, 0.9, 10), [896.73, 54.094, 49.176, 0.0, 0.0]),\n  ('regression: start day one', (0.35, 0.1, 800, 4, 30, 1, 0.7, 12), [519.85, 32.463, 16.687, 231.0, 330.0])],\n [('regression: campaign from day 0',\n   (0.5, 0.25, 2000, 10, 50, 0, 0.8, 20),\n   [872.113, 79.727, 248.159, 800.0, 1000.0]),\n  ('regression: supply exceeds susceptibles',\n   (0.3, 0.1, 100, 2, 80, 1, 0.95, 6),\n   [0.0, 1.516, 1.233, 97.251, 102.369]),\n  ('control: late campaign never starts',\n   (0.3, 0.1, 1000, 5, 100, 50, 0.9, 20),\n   [777.374, 141.242, 81.385, 0.0, 0.0]),\n  ('regression: perfect vaccine small town',\n   (0.6, 0.2, 500, 5, 40, 2, 1.0, 15),\n   [0.0, 10.271, 55.609, 434.12, 434.12]),\n  ('regression: poor vaccine',\n   (0.45, 0.15, 3000, 30, 150, 3, 0.4, 25),\n   [237.471, 307.647, 1134.882, 1320.0, 3300.0]),\n  ('control: no doses', (0.4, 0.2, 1000, 10, 0, 0, 0.9, 10), [896.73, 54.094, 49.176, 0.0, 0.0]),\n  ('regression: start day one', (0.35, 0.1, 800, 4, 30, 1, 0.7, 12), [519.85, 32.463, 16.687, 231.0, 330.0])],\n [('regression: city campaign from day 5',\n   (0.4, 0.2, 10000, 20, 200, 5, 0.9, 30),\n   [4007.174, 324.024, 1168.803, 4500.0, 5000.0]),\n  ('regression: campaign from day 0',\n   (0.5, 0.25, 2000, 10, 50, 0, 0.8, 20),\n   [872.113, 79.727, 248.159, 800.0, 1000.0]),\n  ('control: late campaign never starts',\n   (0.3, 0.1, 1000, 5, 100, 50, 0.9, 20),\n   [777.374, 141.242, 81.385, 0.0, 0.0]),\n  ('regression: perfect vaccine small town',\n   (0.6, 0.2, 500, 5, 40, 2, 1.0, 15),\n   [0.0, 10.271, 55.609, 434.12, 434.12]),\n  ('regression: poor vaccine',\n   (0.45, 0.15, 3000, 30, 150, 3, 0.4, 25),\n   [237.471, 307.647, 1134.882, 1320.0, 3300.0]),\n  ('control: no doses', (0.4, 0.2, 1000, 10, 0, 0, 0.9, 10), [896.73, 54.094, 49.176, 0.0, 0.0]),\n  ('regression: start day one', (0.35, 0.1, 800, 4, 30, 1, 0.7, 12), [519.85, 32.463, 16.687, 231.0, 330.0])]]\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":"Deterministic bounded teaching model with a stipulated contract; not a validated scientific or public-health modelling library. 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-epidemic-vaccine-campaign-efficacy-application","generated_at":"2026-09-29T14:47:30.713542+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Compartmental epidemic calculations drive outbreak forecasts, vaccine targets and hospital planning; a single wrong flow, rate conversion or boundary silently changes every downstream number.","repair":"Restore the efficacy application rule: `s -= dose * efficacy`.","root_cause":"All vaccinees leave S although only effective doses move to V.","sha256":"862ca4205fc3c46ed2f7a46333717fa43a6f76751f5630a33d30a9ee08e62f2a","title":"SIR with daily all-or-nothing vaccination campaign: efficacy application · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":38.728,"exit_code":1,"observations":[{"actual":[5595.024,1353.148,2551.827,4500.0,5000.0],"check":"regression: city campaign from day 5","expected":[4007.174,324.024,1168.803,4500.0,5000.0],"passed":false},{"actual":[1116.656,234.664,448.679,800.0,1000.0],"check":"regression: campaign from day 0","expected":[872.113,79.727,248.159,800.0,1000.0],"passed":false},{"actual":[73.391,4.837,1.859,378.352,398.265],"check":"regression: supply exceeds susceptibles","expected":[0.0,1.516,1.233,97.251,102.369],"passed":false},{"actual":[777.374,141.242,81.385,0.0,0.0],"check":"control: late campaign never starts","expected":[777.374,141.242,81.385,0.0,0.0],"passed":true},{"actual":[141.969,164.262,193.769,520.0,520.0],"check":"regression: perfect vaccine small town","expected":[0.0,10.271,55.609,434.12,434.12],"passed":false},{"actual":[32.671,166.064,860.79,1293.651,3234.127],"check":"regression: poor vaccine","expected":[237.471,307.647,1134.882,1320.0,3300.0],"passed":false},{"actual":[896.73,54.094,49.176,0.0,0.0],"check":"control: no doses","expected":[896.73,54.094,49.176,0.0,0.0],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: city campaign from day 5\", \"actual\": [5595.024, 1353.148, 2551.827, 4500.0, 5000.0], \"expected\": [4007.174, 324.024, 1168.803, 4500.0, 5000.0], \"passed\": false}, {\"check\": \"regression: campaign from day 0\", \"actual\": [1116.656, 234.664, 448.679, 800.0, 1000.0], \"expected\": [872.113, 79.727, 248.159, 800.0, 1000.0], \"passed\": false}, {\"check\": \"regression: supply exceeds susceptibles\", \"actual\": [73.391, 4.837, 1.859, 378.352, 398.265], \"expected\": [0.0, 1.516, 1.233, 97.251, 102.369], \"passed\": false}, {\"check\": \"control: late campaign never starts\", \"actual\": [777.374, 141.242, 81.385, 0.0, 0.0], \"expected\": [777.374, 141.242, 81.385, 0.0, 0.0], \"passed\": true}, {\"check\": \"regression: perfect vaccine small town\", \"actual\": [141.969, 164.262, 193.769, 520.0, 520.0], \"expected\": [0.0, 10.271, 55.609, 434.12, 434.12], \"passed\": false}, {\"check\": \"regression: poor vaccine\", \"actual\": [32.671, 166.064, 860.79, 1293.651, 3234.127], \"expected\": [237.471, 307.647, 1134.882, 1320.0, 3300.0], \"passed\": false}, {\"check\": \"control: no doses\", \"actual\": [896.73, 54.094, 49.176, 0.0, 0.0], \"expected\": [896.73, 54.094, 49.176, 0.0, 0.0], \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":41.758,"exit_code":1,"observations":[{"actual":[3671.765,262.702,1065.533,4500.0,5000.0],"check":"regression: city campaign from day 5","expected":[4007.174,324.024,1168.803,4500.0,5000.0],"passed":false},{"actual":[742.245,52.578,205.177,800.0,1000.0],"check":"regression: campaign from day 0","expected":[872.113,79.727,248.159,800.0,1000.0],"passed":false},{"actual":[0.0,1.492,1.221,92.423,97.287],"check":"regression: supply exceeds susceptibles","expected":[0.0,1.516,1.233,97.251,102.369],"passed":false},{"actual":[777.374,141.242,81.385,0.0,0.0],"check":"control: late campaign never starts","expected":[777.374,141.242,81.385,0.0,0.0],"passed":true},{"actual":[0.0,10.271,55.609,434.12,434.12],"check":"regression: perfect vaccine small town","expected":[0.0,10.271,55.609,434.12,434.12],"passed":true},{"actual":[0.0,51.345,515.176,973.392,2433.479],"check":"regression: poor vaccine","expected":[237.471,307.647,1134.882,1320.0,3300.0],"passed":false},{"actual":[896.73,54.094,49.176,0.0,0.0],"check":"control: no doses","expected":[896.73,54.094,49.176,0.0,0.0],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: city campaign from day 5\", \"actual\": [3671.765, 262.702, 1065.533, 4500.0, 5000.0], \"expected\": [4007.174, 324.024, 1168.803, 4500.0, 5000.0], \"passed\": false}, {\"check\": \"regression: campaign from day 0\", \"actual\": [742.245, 52.578, 205.177, 800.0, 1000.0], \"expected\": [872.113, 79.727, 248.159, 800.0, 1000.0], \"passed\": false}, {\"check\": \"regression: supply exceeds susceptibles\", \"actual\": [0.0, 1.492, 1.221, 92.423, 97.287], \"expected\": [0.0, 1.516, 1.233, 97.251, 102.369], \"passed\": false}, {\"check\": \"control: late campaign never starts\", \"actual\": [777.374, 141.242, 81.385, 0.0, 0.0], \"expected\": [777.374, 141.242, 81.385, 0.0, 0.0], \"passed\": true}, {\"check\": \"regression: perfect vaccine small town\", \"actual\": [0.0, 10.271, 55.609, 434.12, 434.12], \"expected\": [0.0, 10.271, 55.609, 434.12, 434.12], \"passed\": true}, {\"check\": \"regression: poor vaccine\", \"actual\": [0.0, 51.345, 515.176, 973.392, 2433.479], \"expected\": [237.471, 307.647, 1134.882, 1320.0, 3300.0], \"passed\": false}, {\"check\": \"control: no doses\", \"actual\": [896.73, 54.094, 49.176, 0.0, 0.0], \"expected\": [896.73, 54.094, 49.176, 0.0, 0.0], \"passed\": true}], \"passed\": false}\n"},"fixed":{"elapsed_ms":39.445,"exit_code":0,"observations":[{"actual":[4007.174,324.024,1168.803,4500.0,5000.0],"check":"regression: city campaign from day 5","expected":[4007.174,324.024,1168.803,4500.0,5000.0],"passed":true},{"actual":[872.113,79.727,248.159,800.0,1000.0],"check":"regression: campaign from day 0","expected":[872.113,79.727,248.159,800.0,1000.0],"passed":true},{"actual":[0.0,1.516,1.233,97.251,102.369],"check":"regression: supply exceeds susceptibles","expected":[0.0,1.516,1.233,97.251,102.369],"passed":true},{"actual":[777.374,141.242,81.385,0.0,0.0],"check":"control: late campaign never starts","expected":[777.374,141.242,81.385,0.0,0.0],"passed":true},{"actual":[0.0,10.271,55.609,434.12,434.12],"check":"regression: perfect vaccine small town","expected":[0.0,10.271,55.609,434.12,434.12],"passed":true},{"actual":[237.471,307.647,1134.882,1320.0,3300.0],"check":"regression: poor vaccine","expected":[237.471,307.647,1134.882,1320.0,3300.0],"passed":true},{"actual":[896.73,54.094,49.176,0.0,0.0],"check":"control: no doses","expected":[896.73,54.094,49.176,0.0,0.0],"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: city campaign from day 5\", \"actual\": [4007.174, 324.024, 1168.803, 4500.0, 5000.0], \"expected\": [4007.174, 324.024, 1168.803, 4500.0, 5000.0], \"passed\": true}, {\"check\": \"regression: campaign from day 0\", \"actual\": [872.113, 79.727, 248.159, 800.0, 1000.0], \"expected\": [872.113, 79.727, 248.159, 800.0, 1000.0], \"passed\": true}, {\"check\": \"regression: supply exceeds susceptibles\", \"actual\": [0.0, 1.516, 1.233, 97.251, 102.369], \"expected\": [0.0, 1.516, 1.233, 97.251, 102.369], \"passed\": true}, {\"check\": \"control: late campaign never starts\", \"actual\": [777.374, 141.242, 81.385, 0.0, 0.0], \"expected\": [777.374, 141.242, 81.385, 0.0, 0.0], \"passed\": true}, {\"check\": \"regression: perfect vaccine small town\", \"actual\": [0.0, 10.271, 55.609, 434.12, 434.12], \"expected\": [0.0, 10.271, 55.609, 434.12, 434.12], \"passed\": true}, {\"check\": \"regression: poor vaccine\", \"actual\": [237.471, 307.647, 1134.882, 1320.0, 3300.0], \"expected\": [237.471, 307.647, 1134.882, 1320.0, 3300.0], \"passed\": true}, {\"check\": \"control: no doses\", \"actual\": [896.73, 54.094, 49.176, 0.0, 0.0], \"expected\": [896.73, 54.094, 49.176, 0.0, 0.0], \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}