{"abstract":"With large beta*dt the susceptible pool goes negative and recovered exceeds the population.","category":"Epidemic compartment models","checks":7,"contract":"Frequency-dependent SIR integrated with forward Euler at dt=1/substeps; new infections per substep are beta*S*I/pop*dt capped at S; peak prevalence and its day are sampled at day ends (day 0 is the seed); return [S, peak I, peak day, R] rounded to 3 decimals, or None for invalid input.","evaluation_group":"w2-epidemic-sir-substep","failed_approach":"Capping at the whole population is never binding, so the susceptible pool can still go negative.","family":"w2-epidemic-sir-substep-infection-cap","id":"FA-64846","implementations":{"attempt":{"sha256":"8c0239b76073805c5eaec3b9c4887a0228c622228b3417c91d0272d1b64ec59f","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport math\nN = 1\nobservations = []\ndef solve(beta, gamma, pop, i0, days, substeps):\n    if pop <= 0 or i0 < 0 or i0 > pop or substeps < 1:\n        return None\n    dt = 1.0 / substeps\n    s = float(pop - i0)\n    i = float(i0)\n    r = 0.0\n    peak_i = i\n    peak_day = 0\n    for day in range(1, days + 1):\n        for _ in range(substeps):\n            new_inf = min(beta * s * i / pop * dt, pop)\n            new_rec = gamma * i * dt\n            s -= new_inf\n            i += new_inf - new_rec\n            r += new_rec\n        if i > peak_i:\n            peak_i = i\n            peak_day = day\n    return [round(s, 3), round(peak_i, 3), peak_day, round(r, 3)]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('control: mild outbreak in 1000', (0.3, 0.1, 1000, 1, 60, 4), [85.915, 303.71, 39, 810.961]),\n  ('control: fast outbreak daily steps', (0.9, 0.2, 500, 5, 40, 1), [2.433, 249.994, 10, 497.014]),\n  ('control: subcritical seed decays', (0.08, 0.2, 1000, 10, 20, 2), [984.011, 10.0, 0, 15.167]),\n  ('regression: overshoot-prone large beta single step', (3.0, 0.5, 100, 50, 5, 1), [0.0, 75.0, 1, 95.312]),\n  ('control: overshoot-prone large beta two steps', (2.5, 0.3, 200, 80, 6, 2), [0.0, 156.8, 1, 166.339]),\n  ('control: boundary zero days', (0.5, 0.1, 100, 3, 0, 2), [97.0, 3.0, 0, 0.0]),\n  ('control: boundary no seed', (0.5, 0.1, 100, 0, 10, 2), [100.0, 0.0, 0, 0.0])],\n [('regression: overshoot-prone large beta single step', (3.0, 0.5, 100, 50, 5, 1), [0.0, 75.0, 1, 95.312]),\n  ('control: overshoot-prone large beta two steps', (2.5, 0.3, 200, 80, 6, 2), [0.0, 156.8, 1, 166.339]),\n  ('control: boundary zero days', (0.5, 0.1, 100, 3, 0, 2), [97.0, 3.0, 0, 0.0]),\n  ('control: boundary no seed', (0.5, 0.1, 100, 0, 10, 2), [100.0, 0.0, 0, 0.0]),\n  ('control: invalid seed above population', (0.5, 0.1, 100, 150, 10, 2), None),\n  ('control: invalid zero substeps', (0.5, 0.1, 100, 1, 10, 0), None),\n  ('control: slow recovery long run', (0.25, 0.05, 2000, 2, 90, 3), [19.331, 965.817, 43, 1829.639])],\n [('regression: overshoot-prone large beta single step', (3.0, 0.5, 100, 50, 5, 1), [0.0, 75.0, 1, 95.312]),\n  ('control: boundary no seed', (0.5, 0.1, 100, 0, 10, 2), [100.0, 0.0, 0, 0.0]),\n  ('control: invalid seed above population', (0.5, 0.1, 100, 150, 10, 2), None),\n  ('control: invalid zero substeps', (0.5, 0.1, 100, 1, 10, 0), None),\n  ('control: slow recovery long run', (0.25, 0.05, 2000, 2, 90, 3), [19.331, 965.817, 43, 1829.639]),\n  ('control: large city fine steps', (0.4, 0.15, 100000, 20, 50, 8), [13105.196, 25867.476, 37, 75829.968]),\n  ('control: small village', (0.6, 0.25, 50, 1, 30, 2), [5.845, 11.78, 12, 43.206])],\n [('control: mild outbreak in 1000', (0.3, 0.1, 1000, 1, 60, 4), [85.915, 303.71, 39, 810.961]),\n  ('control: fast outbreak daily steps', (0.9, 0.2, 500, 5, 40, 1), [2.433, 249.994, 10, 497.014]),\n  ('regression: overshoot-prone large beta single step', (3.0, 0.5, 100, 50, 5, 1), [0.0, 75.0, 1, 95.312]),\n  ('control: slow recovery long run', (0.25, 0.05, 2000, 2, 90, 3), [19.331, 965.817, 43, 1829.639]),\n  ('control: large city fine steps', (0.4, 0.15, 100000, 20, 50, 8), [13105.196, 25867.476, 37, 75829.968]),\n  ('control: small village', (0.6, 0.25, 50, 1, 30, 2), [5.845, 11.78, 12, 43.206]),\n  ('control: whole population seeded', (0.5, 0.2, 40, 40, 5, 2), [0.0, 40.0, 0, 26.053])],\n [('control: mild outbreak in 1000', (0.3, 0.1, 1000, 1, 60, 4), [85.915, 303.71, 39, 810.961]),\n  ('control: fast outbreak daily steps', (0.9, 0.2, 500, 5, 40, 1), [2.433, 249.994, 10, 497.014]),\n  ('control: subcritical seed decays', (0.08, 0.2, 1000, 10, 20, 2), [984.011, 10.0, 0, 15.167]),\n  ('regression: overshoot-prone large beta single step', (3.0, 0.5, 100, 50, 5, 1), [0.0, 75.0, 1, 95.312]),\n  ('control: overshoot-prone large beta two steps', (2.5, 0.3, 200, 80, 6, 2), [0.0, 156.8, 1, 166.339]),\n  ('control: boundary zero days', (0.5, 0.1, 100, 3, 0, 2), [97.0, 3.0, 0, 0.0]),\n  ('control: whole population seeded', (0.5, 0.2, 40, 40, 5, 2), [0.0, 40.0, 0, 26.053])]]\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":"ba3dcca94a49f237bf2cb6a02cff06c4d580599f6342d3e66d73b4b6e3892a54","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport math\nN = 1\nobservations = []\ndef solve(beta, gamma, pop, i0, days, substeps):\n    if pop <= 0 or i0 < 0 or i0 > pop or substeps < 1:\n        return None\n    dt = 1.0 / substeps\n    s = float(pop - i0)\n    i = float(i0)\n    r = 0.0\n    peak_i = i\n    peak_day = 0\n    for day in range(1, days + 1):\n        for _ in range(substeps):\n            new_inf = beta * s * i / pop * dt\n            new_rec = gamma * i * dt\n            s -= new_inf\n            i += new_inf - new_rec\n            r += new_rec\n        if i > peak_i:\n            peak_i = i\n            peak_day = day\n    return [round(s, 3), round(peak_i, 3), peak_day, round(r, 3)]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('control: mild outbreak in 1000', (0.3, 0.1, 1000, 1, 60, 4), [85.915, 303.71, 39, 810.961]),\n  ('control: fast outbreak daily steps', (0.9, 0.2, 500, 5, 40, 1), [2.433, 249.994, 10, 497.014]),\n  ('control: subcritical seed decays', (0.08, 0.2, 1000, 10, 20, 2), [984.011, 10.0, 0, 15.167]),\n  ('regression: overshoot-prone large beta single step', (3.0, 0.5, 100, 50, 5, 1), [0.0, 75.0, 1, 95.312]),\n  ('control: overshoot-prone large beta two steps', (2.5, 0.3, 200, 80, 6, 2), [0.0, 156.8, 1, 166.339]),\n  ('control: boundary zero days', (0.5, 0.1, 100, 3, 0, 2), [97.0, 3.0, 0, 0.0]),\n  ('control: boundary no seed', (0.5, 0.1, 100, 0, 10, 2), [100.0, 0.0, 0, 0.0])],\n [('regression: overshoot-prone large beta single step', (3.0, 0.5, 100, 50, 5, 1), [0.0, 75.0, 1, 95.312]),\n  ('control: overshoot-prone large beta two steps', (2.5, 0.3, 200, 80, 6, 2), [0.0, 156.8, 1, 166.339]),\n  ('control: boundary zero days', (0.5, 0.1, 100, 3, 0, 2), [97.0, 3.0, 0, 0.0]),\n  ('control: boundary no seed', (0.5, 0.1, 100, 0, 10, 2), [100.0, 0.0, 0, 0.0]),\n  ('control: invalid seed above population', (0.5, 0.1, 100, 150, 10, 2), None),\n  ('control: invalid zero substeps', (0.5, 0.1, 100, 1, 10, 0), None),\n  ('control: slow recovery long run', (0.25, 0.05, 2000, 2, 90, 3), [19.331, 965.817, 43, 1829.639])],\n [('regression: overshoot-prone large beta single step', (3.0, 0.5, 100, 50, 5, 1), [0.0, 75.0, 1, 95.312]),\n  ('control: boundary no seed', (0.5, 0.1, 100, 0, 10, 2), [100.0, 0.0, 0, 0.0]),\n  ('control: invalid seed above population', (0.5, 0.1, 100, 150, 10, 2), None),\n  ('control: invalid zero substeps', (0.5, 0.1, 100, 1, 10, 0), None),\n  ('control: slow recovery long run', (0.25, 0.05, 2000, 2, 90, 3), [19.331, 965.817, 43, 1829.639]),\n  ('control: large city fine steps', (0.4, 0.15, 100000, 20, 50, 8), [13105.196, 25867.476, 37, 75829.968]),\n  ('control: small village', (0.6, 0.25, 50, 1, 30, 2), [5.845, 11.78, 12, 43.206])],\n [('control: mild outbreak in 1000', (0.3, 0.1, 1000, 1, 60, 4), [85.915, 303.71, 39, 810.961]),\n  ('control: fast outbreak daily steps', (0.9, 0.2, 500, 5, 40, 1), [2.433, 249.994, 10, 497.014]),\n  ('regression: overshoot-prone large beta single step', (3.0, 0.5, 100, 50, 5, 1), [0.0, 75.0, 1, 95.312]),\n  ('control: slow recovery long run', (0.25, 0.05, 2000, 2, 90, 3), [19.331, 965.817, 43, 1829.639]),\n  ('control: large city fine steps', (0.4, 0.15, 100000, 20, 50, 8), [13105.196, 25867.476, 37, 75829.968]),\n  ('control: small village', (0.6, 0.25, 50, 1, 30, 2), [5.845, 11.78, 12, 43.206]),\n  ('control: whole population seeded', (0.5, 0.2, 40, 40, 5, 2), [0.0, 40.0, 0, 26.053])],\n [('control: mild outbreak in 1000', (0.3, 0.1, 1000, 1, 60, 4), [85.915, 303.71, 39, 810.961]),\n  ('control: fast outbreak daily steps', (0.9, 0.2, 500, 5, 40, 1), [2.433, 249.994, 10, 497.014]),\n  ('control: subcritical seed decays', (0.08, 0.2, 1000, 10, 20, 2), [984.011, 10.0, 0, 15.167]),\n  ('regression: overshoot-prone large beta single step', (3.0, 0.5, 100, 50, 5, 1), [0.0, 75.0, 1, 95.312]),\n  ('control: overshoot-prone large beta two steps', (2.5, 0.3, 200, 80, 6, 2), [0.0, 156.8, 1, 166.339]),\n  ('control: boundary zero days', (0.5, 0.1, 100, 3, 0, 2), [97.0, 3.0, 0, 0.0]),\n  ('control: whole population seeded', (0.5, 0.2, 40, 40, 5, 2), [0.0, 40.0, 0, 26.053])]]\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":"7bc7d26810559c1701ee07367eb4ab470fb2dfaf8c7472a5bfa82dabe0e44b48","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nimport math\nN = 1\nobservations = []\ndef solve(beta, gamma, pop, i0, days, substeps):\n    if pop <= 0 or i0 < 0 or i0 > pop or substeps < 1:\n        return None\n    dt = 1.0 / substeps\n    s = float(pop - i0)\n    i = float(i0)\n    r = 0.0\n    peak_i = i\n    peak_day = 0\n    for day in range(1, days + 1):\n        for _ in range(substeps):\n            new_inf = min(beta * s * i / pop * dt, s)\n            new_rec = gamma * i * dt\n            s -= new_inf\n            i += new_inf - new_rec\n            r += new_rec\n        if i > peak_i:\n            peak_i = i\n            peak_day = day\n    return [round(s, 3), round(peak_i, 3), peak_day, round(r, 3)]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('control: mild outbreak in 1000', (0.3, 0.1, 1000, 1, 60, 4), [85.915, 303.71, 39, 810.961]),\n  ('control: fast outbreak daily steps', (0.9, 0.2, 500, 5, 40, 1), [2.433, 249.994, 10, 497.014]),\n  ('control: subcritical seed decays', (0.08, 0.2, 1000, 10, 20, 2), [984.011, 10.0, 0, 15.167]),\n  ('regression: overshoot-prone large beta single step', (3.0, 0.5, 100, 50, 5, 1), [0.0, 75.0, 1, 95.312]),\n  ('control: overshoot-prone large beta two steps', (2.5, 0.3, 200, 80, 6, 2), [0.0, 156.8, 1, 166.339]),\n  ('control: boundary zero days', (0.5, 0.1, 100, 3, 0, 2), [97.0, 3.0, 0, 0.0]),\n  ('control: boundary no seed', (0.5, 0.1, 100, 0, 10, 2), [100.0, 0.0, 0, 0.0])],\n [('regression: overshoot-prone large beta single step', (3.0, 0.5, 100, 50, 5, 1), [0.0, 75.0, 1, 95.312]),\n  ('control: overshoot-prone large beta two steps', (2.5, 0.3, 200, 80, 6, 2), [0.0, 156.8, 1, 166.339]),\n  ('control: boundary zero days', (0.5, 0.1, 100, 3, 0, 2), [97.0, 3.0, 0, 0.0]),\n  ('control: boundary no seed', (0.5, 0.1, 100, 0, 10, 2), [100.0, 0.0, 0, 0.0]),\n  ('control: invalid seed above population', (0.5, 0.1, 100, 150, 10, 2), None),\n  ('control: invalid zero substeps', (0.5, 0.1, 100, 1, 10, 0), None),\n  ('control: slow recovery long run', (0.25, 0.05, 2000, 2, 90, 3), [19.331, 965.817, 43, 1829.639])],\n [('regression: overshoot-prone large beta single step', (3.0, 0.5, 100, 50, 5, 1), [0.0, 75.0, 1, 95.312]),\n  ('control: boundary no seed', (0.5, 0.1, 100, 0, 10, 2), [100.0, 0.0, 0, 0.0]),\n  ('control: invalid seed above population', (0.5, 0.1, 100, 150, 10, 2), None),\n  ('control: invalid zero substeps', (0.5, 0.1, 100, 1, 10, 0), None),\n  ('control: slow recovery long run', (0.25, 0.05, 2000, 2, 90, 3), [19.331, 965.817, 43, 1829.639]),\n  ('control: large city fine steps', (0.4, 0.15, 100000, 20, 50, 8), [13105.196, 25867.476, 37, 75829.968]),\n  ('control: small village', (0.6, 0.25, 50, 1, 30, 2), [5.845, 11.78, 12, 43.206])],\n [('control: mild outbreak in 1000', (0.3, 0.1, 1000, 1, 60, 4), [85.915, 303.71, 39, 810.961]),\n  ('control: fast outbreak daily steps', (0.9, 0.2, 500, 5, 40, 1), [2.433, 249.994, 10, 497.014]),\n  ('regression: overshoot-prone large beta single step', (3.0, 0.5, 100, 50, 5, 1), [0.0, 75.0, 1, 95.312]),\n  ('control: slow recovery long run', (0.25, 0.05, 2000, 2, 90, 3), [19.331, 965.817, 43, 1829.639]),\n  ('control: large city fine steps', (0.4, 0.15, 100000, 20, 50, 8), [13105.196, 25867.476, 37, 75829.968]),\n  ('control: small village', (0.6, 0.25, 50, 1, 30, 2), [5.845, 11.78, 12, 43.206]),\n  ('control: whole population seeded', (0.5, 0.2, 40, 40, 5, 2), [0.0, 40.0, 0, 26.053])],\n [('control: mild outbreak in 1000', (0.3, 0.1, 1000, 1, 60, 4), [85.915, 303.71, 39, 810.961]),\n  ('control: fast outbreak daily steps', (0.9, 0.2, 500, 5, 40, 1), [2.433, 249.994, 10, 497.014]),\n  ('control: subcritical seed decays', (0.08, 0.2, 1000, 10, 20, 2), [984.011, 10.0, 0, 15.167]),\n  ('regression: overshoot-prone large beta single step', (3.0, 0.5, 100, 50, 5, 1), [0.0, 75.0, 1, 95.312]),\n  ('control: overshoot-prone large beta two steps', (2.5, 0.3, 200, 80, 6, 2), [0.0, 156.8, 1, 166.339]),\n  ('control: boundary zero days', (0.5, 0.1, 100, 3, 0, 2), [97.0, 3.0, 0, 0.0]),\n  ('control: whole population seeded', (0.5, 0.2, 40, 40, 5, 2), [0.0, 40.0, 0, 26.053])]]\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-sir-substep-infection-cap","generated_at":"2026-09-29T14:47:28.554721+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 infection cap rule: `min(beta * s * i / pop * dt, s)`.","root_cause":"The per-substep infection draw is not capped at the remaining susceptibles.","sha256":"cff9327297291960bea89869d71d25584b9ae830454fee108abb534dc7806e45","title":"SIR Euler integrator with daily sampling: infection cap · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":40.427,"exit_code":1,"observations":[{"actual":[85.915,303.71,39,810.961],"check":"control: mild outbreak in 1000","expected":[85.915,303.71,39,810.961],"passed":true},{"actual":[2.433,249.994,10,497.014],"check":"control: fast outbreak daily steps","expected":[2.433,249.994,10,497.014],"passed":true},{"actual":[984.011,10.0,0,15.167],"check":"control: subcritical seed decays","expected":[984.011,10.0,0,15.167],"passed":true},{"actual":[1244.141,100.0,1,-40.625],"check":"regression: overshoot-prone large beta single step","expected":[0.0,75.0,1,95.312],"passed":false},{"actual":[0.0,156.8,1,166.339],"check":"control: overshoot-prone large beta two steps","expected":[0.0,156.8,1,166.339],"passed":true},{"actual":[97.0,3.0,0,0.0],"check":"control: boundary zero days","expected":[97.0,3.0,0,0.0],"passed":true},{"actual":[100.0,0.0,0,0.0],"check":"control: boundary no seed","expected":[100.0,0.0,0,0.0],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"control: mild outbreak in 1000\", \"actual\": [85.915, 303.71, 39, 810.961], \"expected\": [85.915, 303.71, 39, 810.961], \"passed\": true}, {\"check\": \"control: fast outbreak daily steps\", \"actual\": [2.433, 249.994, 10, 497.014], \"expected\": [2.433, 249.994, 10, 497.014], \"passed\": true}, {\"check\": \"control: subcritical seed decays\", \"actual\": [984.011, 10.0, 0, 15.167], \"expected\": [984.011, 10.0, 0, 15.167], \"passed\": true}, {\"check\": \"regression: overshoot-prone large beta single step\", \"actual\": [1244.141, 100.0, 1, -40.625], \"expected\": [0.0, 75.0, 1, 95.312], \"passed\": false}, {\"check\": \"control: overshoot-prone large beta two steps\", \"actual\": [0.0, 156.8, 1, 166.339], \"expected\": [0.0, 156.8, 1, 166.339], \"passed\": true}, {\"check\": \"control: boundary zero days\", \"actual\": [97.0, 3.0, 0, 0.0], \"expected\": [97.0, 3.0, 0, 0.0], \"passed\": true}, {\"check\": \"control: boundary no seed\", \"actual\": [100.0, 0.0, 0, 0.0], \"expected\": [100.0, 0.0, 0, 0.0], \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":43.333,"exit_code":1,"observations":[{"actual":[85.915,303.71,39,810.961],"check":"control: mild outbreak in 1000","expected":[85.915,303.71,39,810.961],"passed":true},{"actual":[2.433,249.994,10,497.014],"check":"control: fast outbreak daily steps","expected":[2.433,249.994,10,497.014],"passed":true},{"actual":[984.011,10.0,0,15.167],"check":"control: subcritical seed decays","expected":[984.011,10.0,0,15.167],"passed":true},{"actual":[1244.141,100.0,1,-40.625],"check":"regression: overshoot-prone large beta single step","expected":[0.0,75.0,1,95.312],"passed":false},{"actual":[0.0,156.8,1,166.339],"check":"control: overshoot-prone large beta two steps","expected":[0.0,156.8,1,166.339],"passed":true},{"actual":[97.0,3.0,0,0.0],"check":"control: boundary zero days","expected":[97.0,3.0,0,0.0],"passed":true},{"actual":[100.0,0.0,0,0.0],"check":"control: boundary no seed","expected":[100.0,0.0,0,0.0],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"control: mild outbreak in 1000\", \"actual\": [85.915, 303.71, 39, 810.961], \"expected\": [85.915, 303.71, 39, 810.961], \"passed\": true}, {\"check\": \"control: fast outbreak daily steps\", \"actual\": [2.433, 249.994, 10, 497.014], \"expected\": [2.433, 249.994, 10, 497.014], \"passed\": true}, {\"check\": \"control: subcritical seed decays\", \"actual\": [984.011, 10.0, 0, 15.167], \"expected\": [984.011, 10.0, 0, 15.167], \"passed\": true}, {\"check\": \"regression: overshoot-prone large beta single step\", \"actual\": [1244.141, 100.0, 1, -40.625], \"expected\": [0.0, 75.0, 1, 95.312], \"passed\": false}, {\"check\": \"control: overshoot-prone large beta two steps\", \"actual\": [0.0, 156.8, 1, 166.339], \"expected\": [0.0, 156.8, 1, 166.339], \"passed\": true}, {\"check\": \"control: boundary zero days\", \"actual\": [97.0, 3.0, 0, 0.0], \"expected\": [97.0, 3.0, 0, 0.0], \"passed\": true}, {\"check\": \"control: boundary no seed\", \"actual\": [100.0, 0.0, 0, 0.0], \"expected\": [100.0, 0.0, 0, 0.0], \"passed\": true}], \"passed\": false}\n"},"fixed":{"elapsed_ms":41.889,"exit_code":0,"observations":[{"actual":[85.915,303.71,39,810.961],"check":"control: mild outbreak in 1000","expected":[85.915,303.71,39,810.961],"passed":true},{"actual":[2.433,249.994,10,497.014],"check":"control: fast outbreak daily steps","expected":[2.433,249.994,10,497.014],"passed":true},{"actual":[984.011,10.0,0,15.167],"check":"control: subcritical seed decays","expected":[984.011,10.0,0,15.167],"passed":true},{"actual":[0.0,75.0,1,95.312],"check":"regression: overshoot-prone large beta single step","expected":[0.0,75.0,1,95.312],"passed":true},{"actual":[0.0,156.8,1,166.339],"check":"control: overshoot-prone large beta two steps","expected":[0.0,156.8,1,166.339],"passed":true},{"actual":[97.0,3.0,0,0.0],"check":"control: boundary zero days","expected":[97.0,3.0,0,0.0],"passed":true},{"actual":[100.0,0.0,0,0.0],"check":"control: boundary no seed","expected":[100.0,0.0,0,0.0],"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"control: mild outbreak in 1000\", \"actual\": [85.915, 303.71, 39, 810.961], \"expected\": [85.915, 303.71, 39, 810.961], \"passed\": true}, {\"check\": \"control: fast outbreak daily steps\", \"actual\": [2.433, 249.994, 10, 497.014], \"expected\": [2.433, 249.994, 10, 497.014], \"passed\": true}, {\"check\": \"control: subcritical seed decays\", \"actual\": [984.011, 10.0, 0, 15.167], \"expected\": [984.011, 10.0, 0, 15.167], \"passed\": true}, {\"check\": \"regression: overshoot-prone large beta single step\", \"actual\": [0.0, 75.0, 1, 95.312], \"expected\": [0.0, 75.0, 1, 95.312], \"passed\": true}, {\"check\": \"control: overshoot-prone large beta two steps\", \"actual\": [0.0, 156.8, 1, 166.339], \"expected\": [0.0, 156.8, 1, 166.339], \"passed\": true}, {\"check\": \"control: boundary zero days\", \"actual\": [97.0, 3.0, 0, 0.0], \"expected\": [97.0, 3.0, 0, 0.0], \"passed\": true}, {\"check\": \"control: boundary no seed\", \"actual\": [100.0, 0.0, 0, 0.0], \"expected\": [100.0, 0.0, 0, 0.0], \"passed\": true}], \"passed\": true}\n"}},"verified":true,"visibility":"public"}