FAILURE MAP
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FA-12411 / Laboratory measurement reporting / Open access

Piecewise inverse calibration chooses segments by concentration · case 01

Piecewise inverse calibration chooses segments by concentration.

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

ROOT CAUSE

Measured signal is compared against the concentration axis.

VERIFIED REPAIR

Locate the signal interval, then invert that segment using exact interpolation.

Unsuccessful approach: Using only the first calibration segment extrapolates beyond a knot.

Case contract

Knots are strictly increasing concentration and signal integer pairs. Return exact Fraction concentration for an in-range signal; otherwise None. At least two knots.

Why this case matters

A deterministic synthetic laboratory reporting model isolates a software metadata contract; it is not a clinical procedure.

1 / The failure

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json
from fractions import Fraction
N = 1
observations = []
def solve(knots, signal):
    if signal < knots[0][1] or signal > knots[-1][1]:
        return None
    for (x0,y0),(x1,y1) in zip(knots,knots[1:]):
        if signal <= x1:
            return str(Fraction(x0)+Fraction((signal-y0)*(x1-x0),y1-y0))
    return str(knots[-1][0])
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
k=[(0,0),(2*N,4*N),(4*N,12*N)]
check('second segment midpoint', solve(k,8*N), str(3*N))
check('first segment midpoint', solve(k,2*N), str(N))
check('interior knot', solve(k,4*N), str(2*N))
check('upper endpoint', solve(k,12*N), str(4*N))
check('lower endpoint', solve(k,0), '0')
check('below calibration rejected', solve(k,-1), None)
check('above calibration rejected', solve(k,12*N+1), None)
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
second segment midpoint43Failed
first segment midpoint11Passed
interior knot22Passed
upper endpoint44Passed
lower endpoint00Passed
below calibration rejectedNoneNonePassed
above calibration rejectedNoneNonePassed

SHA-256 / 8da77051745a87b63e9c4c4c5dcd6ac81795e6e8cd849fb3c839fa80ea67f670

2 / The unsuccessful fix

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json
from fractions import Fraction
N = 1
observations = []
def solve(knots, signal):
    if signal < knots[0][1] or signal > knots[-1][1]:
        return None
    (x0,y0),(x1,y1) = knots[:2]
    return str(Fraction(x0)+Fraction((signal-y0)*(x1-x0),y1-y0))
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
k=[(0,0),(2*N,4*N),(4*N,12*N)]
check('second segment midpoint', solve(k,8*N), str(3*N))
check('first segment midpoint', solve(k,2*N), str(N))
check('interior knot', solve(k,4*N), str(2*N))
check('upper endpoint', solve(k,12*N), str(4*N))
check('lower endpoint', solve(k,0), '0')
check('below calibration rejected', solve(k,-1), None)
check('above calibration rejected', solve(k,12*N+1), None)
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
second segment midpoint43Failed
first segment midpoint11Passed
interior knot22Passed
upper endpoint64Failed
lower endpoint00Passed
below calibration rejectedNoneNonePassed
above calibration rejectedNoneNonePassed

SHA-256 / 6e3a6adbeb6ec9c3a1c5b737ef086959f9c2de80c18809249d8698f288157b92

3 / The verified repair

Exit 0
"""Failure Map reference implementation. Python standard library only."""
import json
from fractions import Fraction
N = 1
observations = []
def solve(knots, signal):
    if signal < knots[0][1] or signal > knots[-1][1]:
        return None
    for (x0,y0),(x1,y1) in zip(knots,knots[1:]):
        if signal <= y1:
            return str(Fraction(x0)+Fraction((signal-y0)*(x1-x0),y1-y0))
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
k=[(0,0),(2*N,4*N),(4*N,12*N)]
check('second segment midpoint', solve(k,8*N), str(3*N))
check('first segment midpoint', solve(k,2*N), str(N))
check('interior knot', solve(k,4*N), str(2*N))
check('upper endpoint', solve(k,12*N), str(4*N))
check('lower endpoint', solve(k,0), '0')
check('below calibration rejected', solve(k,-1), None)
check('above calibration rejected', solve(k,12*N+1), None)
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
second segment midpoint33Passed
first segment midpoint11Passed
interior knot22Passed
upper endpoint44Passed
lower endpoint00Passed
below calibration rejectedNoneNonePassed
above calibration rejectedNoneNonePassed

SHA-256 / 163957cfe859c4513990b776387d66848164cf07115ecd911aae81f23ff0dae4

Verification & scope

Synthetic integer/rational fixtures only; no instrument validation or clinical interpretation. 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 2026-09-29T14:38:56.685353+00:00.

Case digest / 68b707f37e69de78e0d3f18ff96d7ef8a5fa6497c8d4a1068a78def02dbe2660