Open Problems

Identified gaps in the current program. A collaborator who fills any of these makes a direct contribution to the architecture. To find where each gap sits in the corpus, start from the Guide and widen via the corpus map.

# Gap Layers Priority Notes
1 Human-subject empirical validation of cohort divergence L5 HIGH All current evidence is LLM-mediated. PRISM-B instrument sensitivity confirmed (Run 15); primacy effects bounded as model-specific (F1, GPT-only) and domain-specific (F2, brand-only). Run 15b additionally isolated a JSON-format primacy effect (η² = .217) at the elicitation layer; resolved in sbt-framework v2.3.1 via the dimension_order parameter (Latin-square ordering averages out positional bias). Human conjoint/MaxDiff study with elicited dimensional weights is the next milestone.
2 Long-horizon longitudinal tracking L2L5 MEDIUM H13 closed short-horizon stability across 4 model pairs (cosines > .97). Open: tracking the same cohort across 6+ months and through multiple disruption events to test whether the μ > λ inequality predicts in-vivo trajectories.
3 Real-world agentic deployment L3L4 MEDIUM Exps A/D/Q1 demonstrated compounding and showed constraint framing reduces variance 62% (Q1). Open: field deployment in live agent workflows with revealed-purchase outcomes, beyond simulated agentic commerce.
4 Collapse onset and early-warning indicators L2L5 HIGH R22 closed the recovery side (μ > λ at scale δ restores separability). The symmetric onset problem is open: which observable signals precede the spectral collapse, how early can the gap-decay rate be estimated, and what is the practitioner-facing lead time before separability is lost.
5 Cohort discovery from raw observation L1L5 MEDIUM Most papers stipulate cohorts (priors, demographics, weight vectors). Open: unsupervised identification of latent cohorts from observation streams without pre-specified weights, and conditions under which discovered cohorts coincide with the alibi-style invariant structure.
6 Formal cross-domain operator identification L4 MEDIUM R22 + OST companion cite independent convergence in capital-markets and DeFi composability work showing the same threshold-inequality and projection-operator structure. Open: a formal identification paper showing that brand-perception, organizational verification, and DeFi composability share the same operator-theoretic structure under a specified mapping.
7 Causal identification beyond observational designs L5 MEDIUM All current empirical work is observational and LLM-mediated. Open: quasi-experimental designs (regression-discontinuity around brand events, instrumental variables, natural experiments) that identify the perception-shift effect of a specified disruption rather than its correlation.
8 Multi-shock and cascade dynamics L2L3 LOW R22 models a single coherence shock. Open: interaction effects of sequenced shocks, simultaneous shocks across cohorts, and contagion across linked brands in a portfolio. R21 portfolio immunity result suggests the cascade structure differs for AI vs. human observers.
9 Specification-to-measurement empirical bridge L0L3 MEDIUM SBT v3.2.0 §5.2.1 formalized the DO/WHAT bridge between organizational specification (OST) and observable dimensions (SBT). Open: an empirical study mapping a documented organizational specification onto its measured perception cloud and quantifying specification-perception coupling strength.
10 Capstone synthesis L6 PREMATURE Unified theory review across L0–L5. Premature until human-subject validation (#1) and a longitudinal field result (#2) are in hand.
11 Measurement invariance across observer classes (human vs LLM) L1L5 HIGH Current dimensional-collapse evidence is LLM-mediated and cross-model replicated (R15, cosine .977), and R17 establishes that multi-observer disagreement is itself signal. Open: whether the eight-dimension instrument exhibits configural, metric, and scalar measurement invariance across observer classes — do human and LLM observers load the same dimensions equivalently, or is the LLM aperture a distinct measurement regime? Establishing invariance (or characterizing its bounds) requires calibration against a fixed human reference panel plus convergent-validity tests; absent it, cross-observer-class comparisons of the same brand rest on an unverified equivalence assumption. Distinct from #1 (does cohort divergence replicate with humans) — this tests whether the instrument measures the same construct across observer types.