\section{Limitations}\label{sec:limitations}

\paragraph{Embedding dependence.}
The epiplexity benchmark was run with both mock embeddings (SHA-256
hash-based) and real sentence embeddings (all-MiniLM-L6-v2).  The
results differ dramatically: the biological design loses with mock
embeddings and wins with real embeddings on convergence discrimination.
The real-embedding results use a single model and $N = 100$ trials
(versus $N = 10{,}000$ for mock embeddings); confirmation with
additional embedding models and larger sample sizes would strengthen
the finding.

\paragraph{Synthetic load patterns.}
The metabolism benchmark uses programmatically generated operation
sequences (constant, bursty, gradual, spike).  Real agent workloads
may have different statistical properties---heavier tails, correlated
bursts, priority distributions that differ from our 30\% critical
assumption.

\paragraph{Simulated agents.}
The quorum sensing benchmark simulates agent suspicion signals as
Gaussian draws around known baselines.  Real multi-agent systems have
richer signal environments: suspicion may be autocorrelated, agents
may have heterogeneous detection capabilities, and compromised agents
may adapt their behavior to avoid detection.

\paragraph{No end-to-end evaluation.}
All benchmarks test the structural guarantee mechanisms in isolation.
None runs actual LLM agents performing real tasks.  The guarantees
are validated at the mechanism level, not at the system level.

\paragraph{Manual thresholds.}
Several parameters are manually set rather than auto-calibrated:
the mTOR hysteresis margin ($h = 0.05$), quorum sensing decay
half-life ($5.0$ time units), threshold base ($10.0$), and
epiplexity mixing parameter ($\alpha = 0.5$).  Sensitivity analysis
across these parameters is not provided.

\paragraph{Statistical assumptions.}
Wilson CIs assume independence across trials within seeds.  The
10-seed aggregation partially addresses between-seed variability,
but within-seed trials share the same random number generator state
progression.
