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Computational Validation: IRIS Gate Evo Convergence Data
This document maps each core claim in the manuscript to specific convergence
results from the IRIS Gate Evo
multi-model protocol.
IRIS Gate Evo fires the same compiled prompt to five independent LLM mirrors
(Claude, Gemini, Grok, Mistral, DeepSeek). Models never see each other's
outputs. Convergence is measured server-side by semantic embedding + clustering.
TYPE is assigned by model count: 5/5 = TYPE 0, 4/5 = TYPE 0, 3/5 = TYPE 1,
2/5 = TYPE 2, 1/5 = TYPE 3 (singular).
Two independent IRIS Gate Evo runs passed the S3 convergence gate on the
CBD/VDAC model. Both produced full protocol packages (S4 hypotheses, S5 Monte
Carlo, S6 structured output).
Run
Session ID
S3 Cosine
Outcome
EFSA Stress Test
evo_20260213_035958_pharmacology
0.8569
PASSED
Chronic Dosing
evo_20260213_042930_pharmacology
0.9024
PASSED
Cross-run analysis detected the system's first INDEPENDENT REPLICATION
(cosine 0.789): both runs independently converged on sub-Kd hepatic CBD
concentrations at 50mg/day oral dosing.
Claim-Level Validation
Core Thesis: CBD Is a Universal Mitochondrial Stressor
Manuscript Claim
IRIS Evidence
TYPE
Models
Run
CBD does not discriminate VDAC1 vs VDAC2
>70% transmembrane homology; no published isoform selectivity data
TYPE 0
5/5
EFSA
Membrane partitioning (logP 6.3) is cell-type-indiscriminate
100-1000x enrichment in mitochondrial membranes regardless of cell type
Singular (Claude)
1/5
EFSA
CBD engages both VDAC1 and VDAC2 in all cells
VDAC2 releases BAK in healthy cells too; undermines selectivity argument
At-risk populations (NAFLD, hepatitis, alcohol) need lower limits; healthy do not
Synthesis
Both runs
Both
Open Questions and Known Gaps
Gap
Status
Proposed Experiment
Testability
VDAC1 vs VDAC2 binding selectivity (Kd ratio)
Unknown; predicted <5x by IRIS
MST/ITC in lipid nanodiscs + BAK oligomerization assay
7/10
7-OH-CBD VDAC1 Kd
Unknown; predicted ~10-20 uM (Grok) or weaker (DeepSeek)
MST/SPR binding + Seahorse OCR
5/10
Cumulative ATP deficit independent of GSH
Unresolved; Mistral dissent
Longitudinal ATP/ADP with ROS/GSH clamped via NAC/BSO
6/10
VDAC gating persistence post-washout
Predicted reversible; no direct measurement
Bilayer electrophysiology with washout kinetics
6/10
Monte Carlo Power Analysis
All operationalized hypotheses from both runs achieved statistical power = 1.0
at 300 iterations.
EFSA Stress Test Hypotheses
ID
Description
Effect Size (d)
Power
H1
Membrane enrichment quantification
0.931
1.0
H2
Electrophysiology: gating vs occlusion
1.006
1.0
H3
VDAC1 vs VDAC2 selectivity
0.922
1.0
H4
GSH depletion assay
0.728
1.0
Chronic Dosing Hypotheses
ID
Description
Effect Size (d)
Power
H1
GSH synthesis rate healthy vs NAFLD
1.232
1.0
H2
VDAC1 gating recovery after washout
1.059
1.0
H3
14-day chronic dosing GSH stability
1.349
1.0
H4
7-OH-CBD accumulation & VDAC effects
0.851
1.0
Structural Pattern: Dose-Dependent Isomorphism
The CBD two-pathway model belongs to a structural pattern discovered across
5 independent IRIS Gate Evo runs spanning different molecules:
Molecule
Pattern
Key Variable
CBD
Dose picks pathway; GSH determines outcome
VDAC occupancy vs GSH capacity
Lithium
Low dose neuroprotective; high dose nephrotoxic
GSK-3beta inhibition level
THC
Low CB1 occupancy therapeutic; high occupancy harmful
G-protein vs beta-arrestin bias
Same abstract structure, discovered independently. The molecule is a stress
test; the dose picks the pathway; the tissue context determines the outcome.
How to Reproduce
# Clone the IRIS Gate Evo engine
git clone https://github.com/templetwo/iris-gate-evo.git
# Run data is archived in the findings repo
git clone https://github.com/templetwo/iris-evo-findings.git
# View the specific run data
ls iris-evo-findings/runs/evo_20260213_035958_pharmacology/ # EFSA stress test
ls iris-evo-findings/runs/evo_20260213_042930_pharmacology/ # Chronic dosing# View gold extractions
cat iris-evo-findings/gold/efsa_vdac1_stress_test.md
cat iris-evo-findings/gold/chronic_dosing_gsh_dynamics.md
# Run cross-run convergence analysiscd iris-gate-evo
python cross_run.py --all