FAILURE MAP
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FA-65196 / Epidemic compartment models / Open access

Hospital occupancy from delayed admissions: admission delay direction · case 01

Admissions precede the infections that cause them.

Verified by executionVariant 1 · 7 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

The infection-to-admission delay is applied forward instead of backward.

THE FAILURE

The infection-to-admission delay is applied forward instead of backward.

Unsuccessful approach: Subtracting delay-1 shortens the delay by a day.

Case contract

admissions[t] = hosp_frac*infections[t-delay] (0 before the delay); each admission occupies a bed on days t..t+los-1; return [admissions rounded 4, occupancy rounded 4, earliest peak day].

Why this case matters

Compartmental epidemic calculations drive outbreak forecasts, vaccine targets and hospital planning; a single wrong flow, rate conversion or boundary silently changes every downstream number.

1 / The failure

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(infections, hosp_frac, delay, los):
    n = len(infections)
    adm = [hosp_frac * infections[t + delay] if t + delay < n else 0.0 for t in range(n)]
    occ = []
    for t in range(n):
        lo = max(0, t - los + 1)
        occ.append(round(sum(adm[lo:t + 1]), 4))
    peak = max(range(n), key=lambda t: (occ[t], -t)) if n else None
    return [[round(a, 4) for a in adm], occ, peak]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: wave with 3 day delay',
   ([10, 20, 40, 60, 50, 30, 20, 10, 5], 0.1, 3, 4),
   [[0.0, 0.0, 0.0, 1.0, 2.0, 4.0, 6.0, 5.0, 3.0], [0.0, 0.0, 0.0, 1.0, 3.0, 7.0, 13.0, 17.0, 18.0], 8]),
  ('regression: plateau tie',
   ([10, 10, 10, 10, 10, 10, 10], 0.05, 1, 3),
   [[0.0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.0, 0.5, 1.0, 1.5, 1.5, 1.5, 1.5], 3]),
  ('regression: long stay',
   ([100, 80, 60, 40, 20, 10, 5, 0], 0.03, 2, 6),
   [[0.0, 0.0, 3.0, 2.4, 1.8, 1.2, 0.6, 0.3], [0.0, 0.0, 3.0, 5.4, 7.2, 8.4, 9.0, 9.3], 7]),
  ('control: delay beyond series', ([1, 2, 3], 0.5, 5, 2), [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], 0]),
  ('control: empty series', ([], 0.1, 1, 3), [[], [], None]),
  ('regression: twin peaks',
   ([0, 30, 0, 0, 30, 0, 0, 0], 0.1, 1, 2),
   [[0.0, 0.0, 3.0, 0.0, 0.0, 3.0, 0.0, 0.0], [0.0, 0.0, 3.0, 3.0, 0.0, 3.0, 3.0, 0.0], 2]),
  ('regression: rising',
   ([1, 3, 7, 12, 20, 33], 0.08, 2, 5),
   [[0.0, 0.0, 0.08, 0.24, 0.56, 0.96], [0.0, 0.0, 0.08, 0.32, 0.88, 1.84], 5])],
 [('regression: wave with 3 day delay',
   ([10, 20, 40, 60, 50, 30, 20, 10, 5], 0.1, 3, 4),
   [[0.0, 0.0, 0.0, 1.0, 2.0, 4.0, 6.0, 5.0, 3.0], [0.0, 0.0, 0.0, 1.0, 3.0, 7.0, 13.0, 17.0, 18.0], 8]),
  ('regression: plateau tie',
   ([10, 10, 10, 10, 10, 10, 10], 0.05, 1, 3),
   [[0.0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.0, 0.5, 1.0, 1.5, 1.5, 1.5, 1.5], 3]),
  ('regression: long stay',
   ([100, 80, 60, 40, 20, 10, 5, 0], 0.03, 2, 6),
   [[0.0, 0.0, 3.0, 2.4, 1.8, 1.2, 0.6, 0.3], [0.0, 0.0, 3.0, 5.4, 7.2, 8.4, 9.0, 9.3], 7]),
  ('control: delay beyond series', ([1, 2, 3], 0.5, 5, 2), [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], 0]),
  ('control: empty series', ([], 0.1, 1, 3), [[], [], None]),
  ('regression: twin peaks',
   ([0, 30, 0, 0, 30, 0, 0, 0], 0.1, 1, 2),
   [[0.0, 0.0, 3.0, 0.0, 0.0, 3.0, 0.0, 0.0], [0.0, 0.0, 3.0, 3.0, 0.0, 3.0, 3.0, 0.0], 2]),
  ('regression: rising',
   ([1, 3, 7, 12, 20, 33], 0.08, 2, 5),
   [[0.0, 0.0, 0.08, 0.24, 0.56, 0.96], [0.0, 0.0, 0.08, 0.32, 0.88, 1.84], 5])],
 [('regression: wave with 3 day delay',
   ([10, 20, 40, 60, 50, 30, 20, 10, 5], 0.1, 3, 4),
   [[0.0, 0.0, 0.0, 1.0, 2.0, 4.0, 6.0, 5.0, 3.0], [0.0, 0.0, 0.0, 1.0, 3.0, 7.0, 13.0, 17.0, 18.0], 8]),
  ('regression: plateau tie',
   ([10, 10, 10, 10, 10, 10, 10], 0.05, 1, 3),
   [[0.0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.0, 0.5, 1.0, 1.5, 1.5, 1.5, 1.5], 3]),
  ('regression: long stay',
   ([100, 80, 60, 40, 20, 10, 5, 0], 0.03, 2, 6),
   [[0.0, 0.0, 3.0, 2.4, 1.8, 1.2, 0.6, 0.3], [0.0, 0.0, 3.0, 5.4, 7.2, 8.4, 9.0, 9.3], 7]),
  ('control: delay beyond series', ([1, 2, 3], 0.5, 5, 2), [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], 0]),
  ('control: empty series', ([], 0.1, 1, 3), [[], [], None]),
  ('regression: twin peaks',
   ([0, 30, 0, 0, 30, 0, 0, 0], 0.1, 1, 2),
   [[0.0, 0.0, 3.0, 0.0, 0.0, 3.0, 0.0, 0.0], [0.0, 0.0, 3.0, 3.0, 0.0, 3.0, 3.0, 0.0], 2]),
  ('regression: rising',
   ([1, 3, 7, 12, 20, 33], 0.08, 2, 5),
   [[0.0, 0.0, 0.08, 0.24, 0.56, 0.96], [0.0, 0.0, 0.08, 0.32, 0.88, 1.84], 5])],
 [('regression: wave with 3 day delay',
   ([10, 20, 40, 60, 50, 30, 20, 10, 5], 0.1, 3, 4),
   [[0.0, 0.0, 0.0, 1.0, 2.0, 4.0, 6.0, 5.0, 3.0], [0.0, 0.0, 0.0, 1.0, 3.0, 7.0, 13.0, 17.0, 18.0], 8]),
  ('regression: plateau tie',
   ([10, 10, 10, 10, 10, 10, 10], 0.05, 1, 3),
   [[0.0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.0, 0.5, 1.0, 1.5, 1.5, 1.5, 1.5], 3]),
  ('regression: long stay',
   ([100, 80, 60, 40, 20, 10, 5, 0], 0.03, 2, 6),
   [[0.0, 0.0, 3.0, 2.4, 1.8, 1.2, 0.6, 0.3], [0.0, 0.0, 3.0, 5.4, 7.2, 8.4, 9.0, 9.3], 7]),
  ('control: delay beyond series', ([1, 2, 3], 0.5, 5, 2), [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], 0]),
  ('control: empty series', ([], 0.1, 1, 3), [[], [], None]),
  ('regression: twin peaks',
   ([0, 30, 0, 0, 30, 0, 0, 0], 0.1, 1, 2),
   [[0.0, 0.0, 3.0, 0.0, 0.0, 3.0, 0.0, 0.0], [0.0, 0.0, 3.0, 3.0, 0.0, 3.0, 3.0, 0.0], 2]),
  ('regression: rising',
   ([1, 3, 7, 12, 20, 33], 0.08, 2, 5),
   [[0.0, 0.0, 0.08, 0.24, 0.56, 0.96], [0.0, 0.0, 0.08, 0.32, 0.88, 1.84], 5])],
 [('regression: wave with 3 day delay',
   ([10, 20, 40, 60, 50, 30, 20, 10, 5], 0.1, 3, 4),
   [[0.0, 0.0, 0.0, 1.0, 2.0, 4.0, 6.0, 5.0, 3.0], [0.0, 0.0, 0.0, 1.0, 3.0, 7.0, 13.0, 17.0, 18.0], 8]),
  ('regression: plateau tie',
   ([10, 10, 10, 10, 10, 10, 10], 0.05, 1, 3),
   [[0.0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.0, 0.5, 1.0, 1.5, 1.5, 1.5, 1.5], 3]),
  ('regression: long stay',
   ([100, 80, 60, 40, 20, 10, 5, 0], 0.03, 2, 6),
   [[0.0, 0.0, 3.0, 2.4, 1.8, 1.2, 0.6, 0.3], [0.0, 0.0, 3.0, 5.4, 7.2, 8.4, 9.0, 9.3], 7]),
  ('control: delay beyond series', ([1, 2, 3], 0.5, 5, 2), [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], 0]),
  ('control: empty series', ([], 0.1, 1, 3), [[], [], None]),
  ('regression: twin peaks',
   ([0, 30, 0, 0, 30, 0, 0, 0], 0.1, 1, 2),
   [[0.0, 0.0, 3.0, 0.0, 0.0, 3.0, 0.0, 0.0], [0.0, 0.0, 3.0, 3.0, 0.0, 3.0, 3.0, 0.0], 2]),
  ('regression: rising',
   ([1, 3, 7, 12, 20, 33], 0.08, 2, 5),
   [[0.0, 0.0, 0.08, 0.24, 0.56, 0.96], [0.0, 0.0, 0.08, 0.32, 0.88, 1.84], 5])]]
for label, args, expected in fixtures[N - 1]:
    check(label, solve(*args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
Boundary fixtureActualExpectedOutcome
regression: wave with 3 day delay[[6.0, 5.0, 3.0, 2.0, 1.0, 0.5, 0.0, 0.0, 0.0], [6.0, 11.0, 14.0, 16.0, 11.0, 6.5, 3.5, 1.5, 0.5], 3][[0.0, 0.0, 0.0, 1.0, 2.0, 4.0, 6.0, 5.0, 3.0], [0.0, 0.0, 0.0, 1.0, 3.0, 7.0, 13.0, 17.0, 18.0], 8]Failed
regression: plateau tie[[0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.0], [0.5, 1.0, 1.5, 1.5, 1.5, 1.5, 1.0], 2][[0.0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.0, 0.5, 1.0, 1.5, 1.5, 1.5, 1.5], 3]Failed
regression: long stay[[1.8, 1.2, 0.6, 0.3, 0.15, 0.0, 0.0, 0.0], [1.8, 3.0, 3.6, 3.9, 4.05, 4.05, 2.25, 1.05], 4][[0.0, 0.0, 3.0, 2.4, 1.8, 1.2, 0.6, 0.3], [0.0, 0.0, 3.0, 5.4, 7.2, 8.4, 9.0, 9.3], 7]Failed
control: delay beyond series[[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], 0][[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], 0]Passed
control: empty series[[], [], None][[], [], None]Passed
regression: twin peaks[[3.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 0.0], [3.0, 3.0, 0.0, 3.0, 3.0, 0.0, 0.0, 0.0], 0][[0.0, 0.0, 3.0, 0.0, 0.0, 3.0, 0.0, 0.0], [0.0, 0.0, 3.0, 3.0, 0.0, 3.0, 3.0, 0.0], 2]Failed
regression: rising[[0.56, 0.96, 1.6, 2.64, 0.0, 0.0], [0.56, 1.52, 3.12, 5.76, 5.76, 5.2], 3][[0.0, 0.0, 0.08, 0.24, 0.56, 0.96], [0.0, 0.0, 0.08, 0.32, 0.88, 1.84], 5]Failed

SHA-256 / 51d6a2d572ef071fd12a1715935fe9b8df86d086ff372b37f99cbef65ed0f960

2 / The unsuccessful fix

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(infections, hosp_frac, delay, los):
    n = len(infections)
    adm = [hosp_frac * infections[t - delay + 1] if t - delay + 1 >= 0 else 0.0 for t in range(n)]
    occ = []
    for t in range(n):
        lo = max(0, t - los + 1)
        occ.append(round(sum(adm[lo:t + 1]), 4))
    peak = max(range(n), key=lambda t: (occ[t], -t)) if n else None
    return [[round(a, 4) for a in adm], occ, peak]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: wave with 3 day delay',
   ([10, 20, 40, 60, 50, 30, 20, 10, 5], 0.1, 3, 4),
   [[0.0, 0.0, 0.0, 1.0, 2.0, 4.0, 6.0, 5.0, 3.0], [0.0, 0.0, 0.0, 1.0, 3.0, 7.0, 13.0, 17.0, 18.0], 8]),
  ('regression: plateau tie',
   ([10, 10, 10, 10, 10, 10, 10], 0.05, 1, 3),
   [[0.0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.0, 0.5, 1.0, 1.5, 1.5, 1.5, 1.5], 3]),
  ('regression: long stay',
   ([100, 80, 60, 40, 20, 10, 5, 0], 0.03, 2, 6),
   [[0.0, 0.0, 3.0, 2.4, 1.8, 1.2, 0.6, 0.3], [0.0, 0.0, 3.0, 5.4, 7.2, 8.4, 9.0, 9.3], 7]),
  ('control: delay beyond series', ([1, 2, 3], 0.5, 5, 2), [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], 0]),
  ('control: empty series', ([], 0.1, 1, 3), [[], [], None]),
  ('regression: twin peaks',
   ([0, 30, 0, 0, 30, 0, 0, 0], 0.1, 1, 2),
   [[0.0, 0.0, 3.0, 0.0, 0.0, 3.0, 0.0, 0.0], [0.0, 0.0, 3.0, 3.0, 0.0, 3.0, 3.0, 0.0], 2]),
  ('regression: rising',
   ([1, 3, 7, 12, 20, 33], 0.08, 2, 5),
   [[0.0, 0.0, 0.08, 0.24, 0.56, 0.96], [0.0, 0.0, 0.08, 0.32, 0.88, 1.84], 5])],
 [('regression: wave with 3 day delay',
   ([10, 20, 40, 60, 50, 30, 20, 10, 5], 0.1, 3, 4),
   [[0.0, 0.0, 0.0, 1.0, 2.0, 4.0, 6.0, 5.0, 3.0], [0.0, 0.0, 0.0, 1.0, 3.0, 7.0, 13.0, 17.0, 18.0], 8]),
  ('regression: plateau tie',
   ([10, 10, 10, 10, 10, 10, 10], 0.05, 1, 3),
   [[0.0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.0, 0.5, 1.0, 1.5, 1.5, 1.5, 1.5], 3]),
  ('regression: long stay',
   ([100, 80, 60, 40, 20, 10, 5, 0], 0.03, 2, 6),
   [[0.0, 0.0, 3.0, 2.4, 1.8, 1.2, 0.6, 0.3], [0.0, 0.0, 3.0, 5.4, 7.2, 8.4, 9.0, 9.3], 7]),
  ('control: delay beyond series', ([1, 2, 3], 0.5, 5, 2), [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], 0]),
  ('control: empty series', ([], 0.1, 1, 3), [[], [], None]),
  ('regression: twin peaks',
   ([0, 30, 0, 0, 30, 0, 0, 0], 0.1, 1, 2),
   [[0.0, 0.0, 3.0, 0.0, 0.0, 3.0, 0.0, 0.0], [0.0, 0.0, 3.0, 3.0, 0.0, 3.0, 3.0, 0.0], 2]),
  ('regression: rising',
   ([1, 3, 7, 12, 20, 33], 0.08, 2, 5),
   [[0.0, 0.0, 0.08, 0.24, 0.56, 0.96], [0.0, 0.0, 0.08, 0.32, 0.88, 1.84], 5])],
 [('regression: wave with 3 day delay',
   ([10, 20, 40, 60, 50, 30, 20, 10, 5], 0.1, 3, 4),
   [[0.0, 0.0, 0.0, 1.0, 2.0, 4.0, 6.0, 5.0, 3.0], [0.0, 0.0, 0.0, 1.0, 3.0, 7.0, 13.0, 17.0, 18.0], 8]),
  ('regression: plateau tie',
   ([10, 10, 10, 10, 10, 10, 10], 0.05, 1, 3),
   [[0.0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.0, 0.5, 1.0, 1.5, 1.5, 1.5, 1.5], 3]),
  ('regression: long stay',
   ([100, 80, 60, 40, 20, 10, 5, 0], 0.03, 2, 6),
   [[0.0, 0.0, 3.0, 2.4, 1.8, 1.2, 0.6, 0.3], [0.0, 0.0, 3.0, 5.4, 7.2, 8.4, 9.0, 9.3], 7]),
  ('control: delay beyond series', ([1, 2, 3], 0.5, 5, 2), [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], 0]),
  ('control: empty series', ([], 0.1, 1, 3), [[], [], None]),
  ('regression: twin peaks',
   ([0, 30, 0, 0, 30, 0, 0, 0], 0.1, 1, 2),
   [[0.0, 0.0, 3.0, 0.0, 0.0, 3.0, 0.0, 0.0], [0.0, 0.0, 3.0, 3.0, 0.0, 3.0, 3.0, 0.0], 2]),
  ('regression: rising',
   ([1, 3, 7, 12, 20, 33], 0.08, 2, 5),
   [[0.0, 0.0, 0.08, 0.24, 0.56, 0.96], [0.0, 0.0, 0.08, 0.32, 0.88, 1.84], 5])],
 [('regression: wave with 3 day delay',
   ([10, 20, 40, 60, 50, 30, 20, 10, 5], 0.1, 3, 4),
   [[0.0, 0.0, 0.0, 1.0, 2.0, 4.0, 6.0, 5.0, 3.0], [0.0, 0.0, 0.0, 1.0, 3.0, 7.0, 13.0, 17.0, 18.0], 8]),
  ('regression: plateau tie',
   ([10, 10, 10, 10, 10, 10, 10], 0.05, 1, 3),
   [[0.0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.0, 0.5, 1.0, 1.5, 1.5, 1.5, 1.5], 3]),
  ('regression: long stay',
   ([100, 80, 60, 40, 20, 10, 5, 0], 0.03, 2, 6),
   [[0.0, 0.0, 3.0, 2.4, 1.8, 1.2, 0.6, 0.3], [0.0, 0.0, 3.0, 5.4, 7.2, 8.4, 9.0, 9.3], 7]),
  ('control: delay beyond series', ([1, 2, 3], 0.5, 5, 2), [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], 0]),
  ('control: empty series', ([], 0.1, 1, 3), [[], [], None]),
  ('regression: twin peaks',
   ([0, 30, 0, 0, 30, 0, 0, 0], 0.1, 1, 2),
   [[0.0, 0.0, 3.0, 0.0, 0.0, 3.0, 0.0, 0.0], [0.0, 0.0, 3.0, 3.0, 0.0, 3.0, 3.0, 0.0], 2]),
  ('regression: rising',
   ([1, 3, 7, 12, 20, 33], 0.08, 2, 5),
   [[0.0, 0.0, 0.08, 0.24, 0.56, 0.96], [0.0, 0.0, 0.08, 0.32, 0.88, 1.84], 5])],
 [('regression: wave with 3 day delay',
   ([10, 20, 40, 60, 50, 30, 20, 10, 5], 0.1, 3, 4),
   [[0.0, 0.0, 0.0, 1.0, 2.0, 4.0, 6.0, 5.0, 3.0], [0.0, 0.0, 0.0, 1.0, 3.0, 7.0, 13.0, 17.0, 18.0], 8]),
  ('regression: plateau tie',
   ([10, 10, 10, 10, 10, 10, 10], 0.05, 1, 3),
   [[0.0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.0, 0.5, 1.0, 1.5, 1.5, 1.5, 1.5], 3]),
  ('regression: long stay',
   ([100, 80, 60, 40, 20, 10, 5, 0], 0.03, 2, 6),
   [[0.0, 0.0, 3.0, 2.4, 1.8, 1.2, 0.6, 0.3], [0.0, 0.0, 3.0, 5.4, 7.2, 8.4, 9.0, 9.3], 7]),
  ('control: delay beyond series', ([1, 2, 3], 0.5, 5, 2), [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], 0]),
  ('control: empty series', ([], 0.1, 1, 3), [[], [], None]),
  ('regression: twin peaks',
   ([0, 30, 0, 0, 30, 0, 0, 0], 0.1, 1, 2),
   [[0.0, 0.0, 3.0, 0.0, 0.0, 3.0, 0.0, 0.0], [0.0, 0.0, 3.0, 3.0, 0.0, 3.0, 3.0, 0.0], 2]),
  ('regression: rising',
   ([1, 3, 7, 12, 20, 33], 0.08, 2, 5),
   [[0.0, 0.0, 0.08, 0.24, 0.56, 0.96], [0.0, 0.0, 0.08, 0.32, 0.88, 1.84], 5])]]
for label, args, expected in fixtures[N - 1]:
    check(label, solve(*args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
Boundary fixtureActualExpectedOutcome
regression: wave with 3 day delay[[0.0, 0.0, 1.0, 2.0, 4.0, 6.0, 5.0, 3.0, 2.0], [0.0, 0.0, 1.0, 3.0, 7.0, 13.0, 17.0, 18.0, 16.0], 7][[0.0, 0.0, 0.0, 1.0, 2.0, 4.0, 6.0, 5.0, 3.0], [0.0, 0.0, 0.0, 1.0, 3.0, 7.0, 13.0, 17.0, 18.0], 8]Failed
regression: plateau tie[[0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.5, 1.0, 1.5, 1.5, 1.5, 1.5, 1.5], 2][[0.0, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], [0.0, 0.5, 1.0, 1.5, 1.5, 1.5, 1.5], 3]Failed
regression: long stay[[0.0, 3.0, 2.4, 1.8, 1.2, 0.6, 0.3, 0.15], [0.0, 3.0, 5.4, 7.2, 8.4, 9.0, 9.3, 6.45], 6][[0.0, 0.0, 3.0, 2.4, 1.8, 1.2, 0.6, 0.3], [0.0, 0.0, 3.0, 5.4, 7.2, 8.4, 9.0, 9.3], 7]Failed
control: delay beyond series[[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], 0][[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], 0]Passed
control: empty series[[], [], None][[], [], None]Passed
regression: twin peaks[[0.0, 3.0, 0.0, 0.0, 3.0, 0.0, 0.0, 0.0], [0.0, 3.0, 3.0, 0.0, 3.0, 3.0, 0.0, 0.0], 1][[0.0, 0.0, 3.0, 0.0, 0.0, 3.0, 0.0, 0.0], [0.0, 0.0, 3.0, 3.0, 0.0, 3.0, 3.0, 0.0], 2]Failed
regression: rising[[0.0, 0.08, 0.24, 0.56, 0.96, 1.6], [0.0, 0.08, 0.32, 0.88, 1.84, 3.44], 5][[0.0, 0.0, 0.08, 0.24, 0.56, 0.96], [0.0, 0.0, 0.08, 0.32, 0.88, 1.84], 5]Failed

SHA-256 / e342c2fa608ea88aaac9620f771249ec4f0dd524f688bdd1b671520b7ebd3e3e

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The verified repair and its recorded checks are member-only.

This mechanism has 7 recorded checks per implementation. The open-access tier publishes the failure and the unsuccessful fix; the repaired source that passes every check, and the observations that prove it, are available to members.

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Verification & scope

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.

Observations recorded using Python 3.12.14 at 2026-09-29T14:47:31.740457+00:00.

Case digest / bffd7f2a70ec8cdd5c334668db7f4668cb5e71b36435695dc5f739754211e34d