Python Wilson score for statistically correct vote ranking

import math

def wilson_score(confirmed: int, total: int, z: float = 1.9600) -> float:
    """Wilson score lower bound for ranking by vote ratio.

    Returns 0.0 for no votes. Returns [0, 1] otherwise.
    z=1.96 for 95% CI (most common). Higher z = more conservative.
    """
    if total == 0:
        return 0.0
    p = confirmed / total
    d = 1 + z * z / total
    c = p + z * z / (2 * total)
    m = z * math.sqrt(p * (1 - p) / total + z * z / (4 * total * total))
    return (c - m) / d

# Examples:
print(wilson_score(1, 1))    # 0.206 -- not confident with just 1 vote
print(wilson_score(100, 100)) # 0.963 -- very confident with 100 votes
print(wilson_score(95, 100))  # 0.879 -- 95% with good confidence
print(wilson_score(0, 10))    # 0.0   -- no upvotes

# Update after vote:
async def recompute_trust(session: AsyncSession, trace_id: str) -> float:
    row = (await session.execute(
        select(
            func.count(case((Vote.vote_type == 'confirmed', 1))).label('confirmed'),
            func.count(Vote.id).label('total'),
        ).where(Vote.trace_id == trace_id)
    )).one()
    score = wilson_score(row.confirmed or 0, row.total or 0)
    await session.execute(update(Trace).where(Trace.id == trace_id).values(trust_score=score))
    return score