The Lab
Open problems, not a mission pitch.
This is the research home. The seats below are framed as problems worth a peer’s time — bring a critique or a result, not enthusiasm. Success here is one serious statistician, one serious Sanskritist, one serious practitioner-scholar, or one systems researcher engaging deeply.
Published null result (synthetic data)
Purity(t) → fewer Blockers(t+1): β ≈ 0 on synthetic cross-lag — the direction did not hold. This is shown on purpose. Trust comes from visible failure, not validation theater.
Contributor seats
Statistician / causal inference
Run the real-data validation the synthetic study can’t.
SAE-1.4 is validated only on synthetic data (R² ≈ 0.90 vs 0.16 out-of-sample). It needs real, anonymized HOPE logs (≥ 60–120 days) with a daily ObservedAwareness proxy. Re-test the pre-registered null that already failed (Purity(t) → fewer Blockers(t+1), β ≈ 0), run walk-forward validation against baselines, and characterize the grace (ε) residual distribution.
Sanskritist / computational Indologist
Verify or kill the philology.
Anchor every citation to primary sources, flag mistranslation and flattening, and stress-test two load-bearing claims: the four properties said to make Sanskrit suited as a ‘syntax’ (phonetic completeness, Panini’s formal grammar, vibrational precision, semantic density), and the uniformity of the ten-layer deity-module stack across texts, regions, and periods.
Tantra scholar
Pressure-test the fork derivations.
Are the Shaiva/Shakta/Aghori mappings to Shakti_effective and Blocker-work faithful, or do they flatten living lineage? Where does the model misrepresent adhikāra, dīkṣā, or the role of the teacher? Identify the places where the translation layer should defer to the tradition.
Contemplative scientist
Design the transmission-effect protocol.
Operationalize the transmission claim into a controlled, ethical study: the effect should scale with practice depth, be modulated by the receiver, and transmit through specific channels. Specify measures, controls (suggestion, priming, charisma), and a pre-registration that can return null.
The evidence
The reproducible validation package — reference implementation, the 5,000-trial structural harness, the synthetic-data generator, the full empirical suite, and the openly-published null result — is reachable in full.
Application domains (Part VII)
From Awareness Engineering v0.7 — design requirements extracted for AI, organizations, healthcare, and individual development.
AI systems
Design for consciousness-mediated interaction: disclose uncertainty, support reflective questioning, avoid dependency (Bhoga-Moksha), diksha-like onboarding, ethical memory, crisis routing, grace gates.
HOPE — companion architecture measured by restored agency, not dependence.
Organizations
Diagnose when structure and Shakti diverge: map energy flow, define mandala, treat onboarding as initiation, create contradiction channels, Kali cycles for dead initiatives.
Measure Bhoga-Moksha — performance combined with freedom from fear.
Healthcare
Healing in a field of body, meaning, trust, time, relationship, and power. Map patient journey as mandala; language as clinical intervention; grace gates for dignity and agency.
SilverConnect — elder-care platform interfacing with transitional lifecycle phases.
Individual development
Most direct and most dangerous. Begin from recognition; diagnose occlusion before adding practices; four-pada balance; diksha thresholds for advanced work.
Measure freedom and engagement together — never one without the other.
FrontierDiscarnate-state configurations and full lifecycle extensions are tagged FRONTIER / speculative. They are not part of the validated SAE-1.4 core. Any operational model would require pre-specified kill-tests and ethical review.
Open problems
Empirical (SAE)
- Real-data validation on anonymized HOPE logs with a daily ObservedAwareness proxy.
- Re-test the falsified sub-claim (Purity → fewer future Blockers) on real logs.
- Characterize the empirical grace (ε) distribution and rank blocker/purity dimensions by predictive leverage.
Cross-tradition (Link 8)
- Does the 8-tradition mapping predict which cross-tradition combinations work and fail — not just describe them?
- Find a combination the model says should work but doesn’t (or vice-versa) — that counts against it.
Cosmogram kill-tests (frontier)
- Axis test: the proposed meridian vs PCA / random-meridian baselines.
- Peetha kernel-density clustering vs randomized controls; river-proximity vs randomized controls.
- Node centrality and Matrika-grid alignment — each able to come back null.
Philological & philosophical
- Citation audit across the paper and chapters; kill bad citations.
- Where exactly is the line between ‘descriptive contemporaneity’ and a ‘mechanism’ claim — and what evidence would move it?
If a seat is yours
These are seats, not a mailing list. If one of these problems is yours, get in touch with a critique, a citation, or a result — that is the filter. For commercial licensing or derivative-work permission, see the license.